A basic, domain-agnostic standard which can be easily understood and implemented, and as such is one of the best known and most widely used metadata standards.
Sponsored by the Dublin Core Metadata Initiative, Dublin Core was published as ISO Sta', 'https://rdamsc.bath.ac.uk/api2/m15', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('JATS', 'The Tag Libraries provide interactive documentation for this Tag Set that you can access through Web browsers. Separate Tag Libraries have been set up for each of the specific Tag Sets (Journal Archiving, Journal Publishing, and Article Authoring).', 'https://jats.nlm.nih.gov/archiving/tag-library/1.2/chapter/nfd-journal-meta.html', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Metadados segundo padrão do Repositório USP', 'Metadados segundo padrão do Repositório USP, incluindo descrição das variáveis (identificação do animal, idade, peso, altura da cernelha, largura da garupa, concentração sérica de IgG), unidades de medida, datas de coleta e métodos laboratoriais utilizado', 'https://repositorio.usp.br/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('NIH DMSP Element 3 Metadata Standards', 'Metadata includes README files, statistical analysis plans, and codebooks describing variables, transformations, and software environments.', 'https://dataworks.faseb.org/helpdesk/kb/element-3-data-standards', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Internal REDCap and Project-Level Metadata', 'Metadata includes audio file identifiers, timestamps, interview context, and links to corresponding transcripts. Maintained internally.', 'https://wiki.ohsu.edu/pages/viewpage.action?pageId=159191839', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('NIH FAIR Metadata Principles', 'Metadata will include README files describing interview context, coding schema, and anonymization procedures, supporting reuse and transparency.', 'https://www.niaid.nih.gov/research/fair-data-principles', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('REDCap Metadata & Data Dictionary', ' REDCap metadata includes structured definitions of survey instruments, field attributes, variable names, branching logic, and event mappings. The data dictionary provides a CSV-formatted file that defines all variables used in the survey, supporting repr', 'https://project-redcap.org', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('American University of Sharjah Institutional Repository', 'The AUS Institutional Repository (DSpace) follows standard metadata practices (Dublin Core) to ensure research outputs are discoverable, citable, and preserved for long-term access. Deposited items include bibliographic information (title, author, abstrac', 'https://dspace.aus.edu', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Learning Resource Metadata Initiative', 'The LRMI specification is a collection of classes, properties and concept schemes for markup and description of educational resources. This vocabulary is designed to be used alongside other resource description vocabularies such as those provided by DCMI,', 'https://www.dublincore.org/about/lrmi/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CodeMeta 2.0', 'CodeMeta contributors are creating a minimal metadata schema for science software and code, in JSON and XML. The goal of CodeMeta is to create a concept vocabulary that can be used to standardize the exchange of software metadata across repositories and o', 'https://github.com/codemeta/codemeta', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OpenAPI 3.1', 'The OpenAPI Specification (OAS) defines a standard, language-agnostic interface to HTTP APIs which allows both humans and computers to discover and understand the capabilities of the service without access to source code, documentation, or through network', 'https://spec.openapis.org/oas/v3.1.0.html', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OWL Web Ontology Language', 'A semantic markup language for publishing and sharing ontologies on the World Wide Web.', 'https://www.w3.org/TR/owl-ref/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CODAS', 'FDFDf', 'fasdfdf', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('(GA4GH) Global Alliance for Genomics and Health ', 'GA4GH (Global Alliance for Genomics and Health) is an international coalition that develops standards, tools, and frameworks to enable the responsible, secure, and effective sharing of genomic and health-related data. Its goal is to accelerate research an', 'https://www.ga4gh.org/how-we-work/standards/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('PRONOM', 'PRONOM is an on-line information system about file formats and how to identify them. Originally developed to support the accession and long-term preservation of electronic records held by the National Archives, PRONOM is a resource available for anyone re', 'https://www.nationalarchives.gov.uk/pronom/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('PBCore', 'pbcoreDescription is an element that uses free-form text or a narrative to report general notes, abstracts, or summaries about the intellectual content of an asset. The information may be in the form of an individual program description, anecdotal interpr', 'https://pbcore.org', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('METS (Metadata Encoding and Transmission Standard)', 'The METS schema is a standard test for encoding descriptive, administrative, and structural metadata regarding objects within a digital library, expressed using the XML schema language of the World Wide Web Consortium. The standard is maintained by the ME', 'https://www.loc.gov/standards/mets/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('STAC 1.2.0', 'STAC Versioning Indicators Extension for STAC Items and STAC Collections.', 'https://stac-extensions.github.io/version/v1.2.0/schema.json', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CrossRef', 'Crossref runs open infrastructure to link research objects, entities, and actions, creating a lasting and reusable scholarly record that underpins open science. Together with our 22,000 members in 160 countries, we drive metadata exchange and support near', 'https://www.crossref.org/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CESSDA Data Catalogue DDI Profiles', 'The profiles specify the metadata requirements of the CESSDA Data Catalogue, based on the CESSDA Metadata Model and the DDI specifications.', 'https://rdamsc.bath.ac.uk/api2/m121', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('JSON-LD (JavaScript Object Notation for Linked Data)', 'Refers to a concept for the use of linked data. It is based on the JSON format and extends this. With JSON-LD, data can be annotated for automatic exchange between web applications and web services, and properly used, data in JSON-LD can be expressed as L', 'https://rdamsc.bath.ac.uk/api2/m95', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('DDI (Data Documentation Initiative)', '
A widely used, international standard for describing data from the social, behavioral, and economic sciences. Two versions of the standard are currently maintained in parallel:
A reference framework that provides a common terminology acroos and between statistical organisations; aligns with DDI and SDMX.
', 'https://rdamsc.bath.ac.uk/api2/m63', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('ISO 19115', 'An internationally-adopted schema for describing geographic information and services. It provides information about the identification, the extent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic ', 'https://rdamsc.bath.ac.uk/api2/m22', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('schema.org', ' Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond. Schema.org vocabulary can be used with many different encodings', 'https://rdamsc.bath.ac.uk/api2/m101', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('iFDO - image FAIR Digital Object', 'Achieving FAIRness and Openness of (marine) image data requires structured and standardised metadata on the image data itself and the visual and semantic image data content. This metadata shall be provided in the form of FAIR digital objects (FDOs). ', 'https://rdamsc.bath.ac.uk/api2/m134', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('ISO 19115-3 - XML schema implementation for fundamental concepts', 'An internationally-adopted schema for describing geographic information and services. It provides information about the identification, the extent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic dat', 'https://rdamsc.bath.ac.uk/api2/m133', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Terminal RI Unicamp', 'Institutional Repository from Unicamp', 'https://repositorio.unicamp.br/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OHDSI Phenotyping Algorythm', 'An OHDSI standardized rule-based cohort definition explicitly stating one or more inclusion criteria in a specific duration of time. Represented using a combination of SQL, JSON, and/or CapR R code formatted for use by the HADES CohortGenerator R package.', 'https://github.com/OHDSI/CohortGenerator', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Marine Community Profile', '
A profile that was developed in accordance with ISO 19115 rules by the Australian Ocean Data Centre Joint Facility (AODCJF) that supported the documentation and discovery of marine spatial datasets. Management of more recent versions of the profile wa', 'https://rdamsc.bath.ac.uk/api2/m71', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('geocore', 'The geocore format is a standardless format that is able to store various metadata fields. It is based on the geoJSON format where the properties field of the geoJSON file stores the metadata for each record.', 'https://rdamsc.bath.ac.uk/api2/m132', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OEMetadata (Open Energy Metadata)', 'Open Energy Metadata (OEMetadata) is a metadata standard for the energy domain. It is an extensive set of metadata based on the tabular data package specifications and the FAIR principles. It is mainly developed for the Open Energy Platform (OEP).', 'https://rdamsc.bath.ac.uk/api2/m128', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Sintomas osteomusculares', 'Gestão de dados científicos', 'https://prpi.usp.br/gestao-de-dados-cientificos/?codmnu=9979', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Integrated Matadeta Infrastructure (DDI + ISO 19115 + Omop CDM)', 'This hybrid standard combines three supplementary protocols to fully document the integrated data of your study: DDI (data documentation initiative) For survey variables (contact diary, demographics). Question words, response options, and logic. Socia', 'DDI: https://ddialliance.org, ISO 19115: https://www.iso.org/standard/53798.html, OMOP CDM: https://ohdsi.github.io/CommonDataModel', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('National Microbiome Data Collective', 'Complex data from microbial genomes, proteins, and metabolites provide a window into the microbial world. Yet these data are scattered and difficult to access among scientists and databases. The NMDC makes these datasets findable, accessible, interoperabl', 'https://microbiomedata.org/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('PLOS One', 'Peer-reviewed open access mega journal published by the Public Library of Science', 'https://journals.plos.org/plosone/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('NOAA’s National Centers for Environmental Information’s Marine Microplastic Database', 'Central database for microplastic and marine debris distribution.', 'https://www.ncei.noaa.gov/products/microplastics', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CIMR (Core Information for Metabolomics Reporting)', 'CIMR was developed by the Metabolomics Standards Initiative (MSI) to specify guidelines for the minimum information to include when reporting metabolomics work. It was developed in textual form, but work is underway to develop a data model, exchange forma', 'https://rdamsc.bath.ac.uk/api2/m130', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('MIxS (Minimum Information about Any Sequence)', '
MIxS is a superset of metadata elements that can be used to compile minimum information checklists for reporting sequencing data. It was developed by the Genomic Standards Consortium (GSC) as an overarching framework that could act as a single entry po', 'https://rdamsc.bath.ac.uk/api2/m108', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('MOD (Metadata for Ontology Description and Publication Ontology)', 'MOD (Metadata for Ontology Description and Publication Ontology) is a metadata schema designed to describe semantic artefacts, such as ontologies, vocabularies, and terminologies, in a standardized and FAIR-compliant way. Developed in the RDA Vocabulary S', 'https://rdamsc.bath.ac.uk/api2/m129', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('GIATE (Guidelines for Information About Therapy Experiments)', 'GIATE is a minimum information checklist for transparently reporting the purpose, methods and results of the therapeutic experiments. Resources are provided for compiling metadata records in spreadsheet form (GIATE-TAB), rather than using a machine-readab', 'https://rdamsc.bath.ac.uk/api2/m131', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('ODAM Structural Metadata', 'Open Data for Access and Mining (ODAM) Structural Metadata is a format describing how the metadata should be formatted and what should be included to ensure ODAM compliance for a data set. To comply with this format, two metadata files in TSV format are r', 'https://rdamsc.bath.ac.uk/api2/m127', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('DCAT (Data Catalog Vocabulary)', '
By using DCAT to describe datasets in data catalogs, publishers are using a standard model and vocabulary that facilitates the consumption and aggregation of metadata from multiple catalogs, and in doing so can increase the discoverability of datasets.', 'https://rdamsc.bath.ac.uk/api2/m12', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Data Package', '
The Data Package specification is a generic wrapper format for exchanging data. Although it supports arbitrary metadata, the format defines required, recommended, and optional fields for both the package as a whole and the resources contained within it', 'https://rdamsc.bath.ac.uk/api2/m10', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('MIBBI (Minimum Information for Biological and Biomedical Investigations)', '
The MIBBI Project was an international collaboration seeking to harmonize the efforts of the various bioscience communities developing Minimum Information (MI) reporting guidelines or checklists. Approximately 40 such checklists registered with the pro', 'https://rdamsc.bath.ac.uk/api2/m23', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Internal README & Document Header', 'Alle essenziellen Metadaten (Interview-ID, Datum, Dauer, Rolle / Pseudonym, Transkriptionsregeln, Anonymisierungshinweise, Kontakt) werden in einer zentralen README-Datei sowie als Header in jedem Transkript gepflegt. Kein externer Metadaten-Standard erfo', 'n/a (project-internal)', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('FGDC Metadata Standard', 'Meets expectation of the FGDC metadata standard (FGDC-STD-001-1998)', 'https://mrdata.usgs.gov', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('e-PMG – Padrão de Metadados do Governo Eletrônico', 'This guide specifies the e-Government Metadata Standard (e-PMG), establishing the semantics of the elements, qualifiers and how to use them to description of informational resources.', 'https://www.gov.br/governodigital/pt-br/infraestrutura-nacional-de-dados/PMGVersao1_1.pdf', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('DDI Stanard ', 'DDI Metadata', 'www.madeupaddress.com', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Camera Trap Metadata Standard', 'open data standard for storing and sharing camera trap data', 'https://bdj.pensoft.net/article/10197/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CS3DP', 'Creation and use of 3D applications and data in research over the last decade leading has exploded, but at the same time, there has been little available guidance regarding the preservation of 3D digital objects and associated information in perpetuity. S', 'https://cs3dp.org/', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Dublin Core', '
A basic, domain-agnostic standard which can be easily understood and implemented, and as such is one of the best known and most widely used metadata standards.
Sponsored by the Dublin Core Metadata Initiative, Dublin Core was published as ISO Sta', 'https://rdamsc.bath.ac.uk/api2/m15', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('JATS', 'The Tag Libraries provide interactive documentation for this Tag Set that you can access through Web browsers. Separate Tag Libraries have been set up for each of the specific Tag Sets (Journal Archiving, Journal Publishing, and Article Authoring).', 'https://jats.nlm.nih.gov/archiving/tag-library/1.2/chapter/nfd-journal-meta.html', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Metadados segundo padrão do Repositório USP', 'Metadados segundo padrão do Repositório USP, incluindo descrição das variáveis (identificação do animal, idade, peso, altura da cernelha, largura da garupa, concentração sérica de IgG), unidades de medida, datas de coleta e métodos laboratoriais utilizado', 'https://repositorio.usp.br/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('NIH DMSP Element 3 Metadata Standards', 'Metadata includes README files, statistical analysis plans, and codebooks describing variables, transformations, and software environments.', 'https://dataworks.faseb.org/helpdesk/kb/element-3-data-standards', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Internal REDCap and Project-Level Metadata', 'Metadata includes audio file identifiers, timestamps, interview context, and links to corresponding transcripts. Maintained internally.', 'https://wiki.ohsu.edu/pages/viewpage.action?pageId=159191839', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('NIH FAIR Metadata Principles', 'Metadata will include README files describing interview context, coding schema, and anonymization procedures, supporting reuse and transparency.', 'https://www.niaid.nih.gov/research/fair-data-principles', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('REDCap Metadata & Data Dictionary', ' REDCap metadata includes structured definitions of survey instruments, field attributes, variable names, branching logic, and event mappings. The data dictionary provides a CSV-formatted file that defines all variables used in the survey, supporting repr', 'https://project-redcap.org', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('American University of Sharjah Institutional Repository', 'The AUS Institutional Repository (DSpace) follows standard metadata practices (Dublin Core) to ensure research outputs are discoverable, citable, and preserved for long-term access. Deposited items include bibliographic information (title, author, abstrac', 'https://dspace.aus.edu', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Learning Resource Metadata Initiative', 'The LRMI specification is a collection of classes, properties and concept schemes for markup and description of educational resources. This vocabulary is designed to be used alongside other resource description vocabularies such as those provided by DCMI,', 'https://www.dublincore.org/about/lrmi/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CodeMeta 2.0', 'CodeMeta contributors are creating a minimal metadata schema for science software and code, in JSON and XML. The goal of CodeMeta is to create a concept vocabulary that can be used to standardize the exchange of software metadata across repositories and o', 'https://github.com/codemeta/codemeta', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OpenAPI 3.1', 'The OpenAPI Specification (OAS) defines a standard, language-agnostic interface to HTTP APIs which allows both humans and computers to discover and understand the capabilities of the service without access to source code, documentation, or through network', 'https://spec.openapis.org/oas/v3.1.0.html', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OWL Web Ontology Language', 'A semantic markup language for publishing and sharing ontologies on the World Wide Web.', 'https://www.w3.org/TR/owl-ref/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CODAS', 'FDFDf', 'fasdfdf', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('(GA4GH) Global Alliance for Genomics and Health ', 'GA4GH (Global Alliance for Genomics and Health) is an international coalition that develops standards, tools, and frameworks to enable the responsible, secure, and effective sharing of genomic and health-related data. Its goal is to accelerate research an', 'https://www.ga4gh.org/how-we-work/standards/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('PRONOM', 'PRONOM is an on-line information system about file formats and how to identify them. Originally developed to support the accession and long-term preservation of electronic records held by the National Archives, PRONOM is a resource available for anyone re', 'https://www.nationalarchives.gov.uk/pronom/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('PBCore', 'pbcoreDescription is an element that uses free-form text or a narrative to report general notes, abstracts, or summaries about the intellectual content of an asset. The information may be in the form of an individual program description, anecdotal interpr', 'https://pbcore.org', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('METS (Metadata Encoding and Transmission Standard)', 'The METS schema is a standard test for encoding descriptive, administrative, and structural metadata regarding objects within a digital library, expressed using the XML schema language of the World Wide Web Consortium. The standard is maintained by the ME', 'https://www.loc.gov/standards/mets/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('STAC 1.2.0', 'STAC Versioning Indicators Extension for STAC Items and STAC Collections.', 'https://stac-extensions.github.io/version/v1.2.0/schema.json', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CrossRef', 'Crossref runs open infrastructure to link research objects, entities, and actions, creating a lasting and reusable scholarly record that underpins open science. Together with our 22,000 members in 160 countries, we drive metadata exchange and support near', 'https://www.crossref.org/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CESSDA Data Catalogue DDI Profiles', 'The profiles specify the metadata requirements of the CESSDA Data Catalogue, based on the CESSDA Metadata Model and the DDI specifications.', 'https://rdamsc.bath.ac.uk/api2/m121', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('JSON-LD (JavaScript Object Notation for Linked Data)', 'Refers to a concept for the use of linked data. It is based on the JSON format and extends this. With JSON-LD, data can be annotated for automatic exchange between web applications and web services, and properly used, data in JSON-LD can be expressed as L', 'https://rdamsc.bath.ac.uk/api2/m95', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('DDI (Data Documentation Initiative)', '
A widely used, international standard for describing data from the social, behavioral, and economic sciences. Two versions of the standard are currently maintained in parallel:
A reference framework that provides a common terminology acroos and between statistical organisations; aligns with DDI and SDMX.
', 'https://rdamsc.bath.ac.uk/api2/m63', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('ISO 19115', 'An internationally-adopted schema for describing geographic information and services. It provides information about the identification, the extent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic ', 'https://rdamsc.bath.ac.uk/api2/m22', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('schema.org', ' Schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond. Schema.org vocabulary can be used with many different encodings', 'https://rdamsc.bath.ac.uk/api2/m101', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('iFDO - image FAIR Digital Object', 'Achieving FAIRness and Openness of (marine) image data requires structured and standardised metadata on the image data itself and the visual and semantic image data content. This metadata shall be provided in the form of FAIR digital objects (FDOs). ', 'https://rdamsc.bath.ac.uk/api2/m134', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('ISO 19115-3 - XML schema implementation for fundamental concepts', 'An internationally-adopted schema for describing geographic information and services. It provides information about the identification, the extent, the quality, the spatial and temporal schema, spatial reference, and distribution of digital geographic dat', 'https://rdamsc.bath.ac.uk/api2/m133', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Terminal RI Unicamp', 'Institutional Repository from Unicamp', 'https://repositorio.unicamp.br/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OHDSI Phenotyping Algorythm', 'An OHDSI standardized rule-based cohort definition explicitly stating one or more inclusion criteria in a specific duration of time. Represented using a combination of SQL, JSON, and/or CapR R code formatted for use by the HADES CohortGenerator R package.', 'https://github.com/OHDSI/CohortGenerator', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Marine Community Profile', '
A profile that was developed in accordance with ISO 19115 rules by the Australian Ocean Data Centre Joint Facility (AODCJF) that supported the documentation and discovery of marine spatial datasets. Management of more recent versions of the profile wa', 'https://rdamsc.bath.ac.uk/api2/m71', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('geocore', 'The geocore format is a standardless format that is able to store various metadata fields. It is based on the geoJSON format where the properties field of the geoJSON file stores the metadata for each record.', 'https://rdamsc.bath.ac.uk/api2/m132', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('OEMetadata (Open Energy Metadata)', 'Open Energy Metadata (OEMetadata) is a metadata standard for the energy domain. It is an extensive set of metadata based on the tabular data package specifications and the FAIR principles. It is mainly developed for the Open Energy Platform (OEP).', 'https://rdamsc.bath.ac.uk/api2/m128', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Sintomas osteomusculares', 'Gestão de dados científicos', 'https://prpi.usp.br/gestao-de-dados-cientificos/?codmnu=9979', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Integrated Matadeta Infrastructure (DDI + ISO 19115 + Omop CDM)', 'This hybrid standard combines three supplementary protocols to fully document the integrated data of your study: DDI (data documentation initiative) For survey variables (contact diary, demographics). Question words, response options, and logic. Socia', 'DDI: https://ddialliance.org, ISO 19115: https://www.iso.org/standard/53798.html, OMOP CDM: https://ohdsi.github.io/CommonDataModel', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('National Microbiome Data Collective', 'Complex data from microbial genomes, proteins, and metabolites provide a window into the microbial world. Yet these data are scattered and difficult to access among scientists and databases. The NMDC makes these datasets findable, accessible, interoperabl', 'https://microbiomedata.org/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('PLOS One', 'Peer-reviewed open access mega journal published by the Public Library of Science', 'https://journals.plos.org/plosone/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('NOAA’s National Centers for Environmental Information’s Marine Microplastic Database', 'Central database for microplastic and marine debris distribution.', 'https://www.ncei.noaa.gov/products/microplastics', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CIMR (Core Information for Metabolomics Reporting)', 'CIMR was developed by the Metabolomics Standards Initiative (MSI) to specify guidelines for the minimum information to include when reporting metabolomics work. It was developed in textual form, but work is underway to develop a data model, exchange forma', 'https://rdamsc.bath.ac.uk/api2/m130', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('MIxS (Minimum Information about Any Sequence)', '
MIxS is a superset of metadata elements that can be used to compile minimum information checklists for reporting sequencing data. It was developed by the Genomic Standards Consortium (GSC) as an overarching framework that could act as a single entry po', 'https://rdamsc.bath.ac.uk/api2/m108', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('MOD (Metadata for Ontology Description and Publication Ontology)', 'MOD (Metadata for Ontology Description and Publication Ontology) is a metadata schema designed to describe semantic artefacts, such as ontologies, vocabularies, and terminologies, in a standardized and FAIR-compliant way. Developed in the RDA Vocabulary S', 'https://rdamsc.bath.ac.uk/api2/m129', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('GIATE (Guidelines for Information About Therapy Experiments)', 'GIATE is a minimum information checklist for transparently reporting the purpose, methods and results of the therapeutic experiments. Resources are provided for compiling metadata records in spreadsheet form (GIATE-TAB), rather than using a machine-readab', 'https://rdamsc.bath.ac.uk/api2/m131', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('ODAM Structural Metadata', 'Open Data for Access and Mining (ODAM) Structural Metadata is a format describing how the metadata should be formatted and what should be included to ensure ODAM compliance for a data set. To comply with this format, two metadata files in TSV format are r', 'https://rdamsc.bath.ac.uk/api2/m127', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('DCAT (Data Catalog Vocabulary)', '
By using DCAT to describe datasets in data catalogs, publishers are using a standard model and vocabulary that facilitates the consumption and aggregation of metadata from multiple catalogs, and in doing so can increase the discoverability of datasets.', 'https://rdamsc.bath.ac.uk/api2/m12', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Data Package', '
The Data Package specification is a generic wrapper format for exchanging data. Although it supports arbitrary metadata, the format defines required, recommended, and optional fields for both the package as a whole and the resources contained within it', 'https://rdamsc.bath.ac.uk/api2/m10', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('MIBBI (Minimum Information for Biological and Biomedical Investigations)', '
The MIBBI Project was an international collaboration seeking to harmonize the efforts of the various bioscience communities developing Minimum Information (MI) reporting guidelines or checklists. Approximately 40 such checklists registered with the pro', 'https://rdamsc.bath.ac.uk/api2/m23', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Internal README & Document Header', 'Alle essenziellen Metadaten (Interview-ID, Datum, Dauer, Rolle / Pseudonym, Transkriptionsregeln, Anonymisierungshinweise, Kontakt) werden in einer zentralen README-Datei sowie als Header in jedem Transkript gepflegt. Kein externer Metadaten-Standard erfo', 'n/a (project-internal)', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('FGDC Metadata Standard', 'Meets expectation of the FGDC metadata standard (FGDC-STD-001-1998)', 'https://mrdata.usgs.gov', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('e-PMG – Padrão de Metadados do Governo Eletrônico', 'This guide specifies the e-Government Metadata Standard (e-PMG), establishing the semantics of the elements, qualifiers and how to use them to description of informational resources.', 'https://www.gov.br/governodigital/pt-br/infraestrutura-nacional-de-dados/PMGVersao1_1.pdf', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('DDI Stanard ', 'DDI Metadata', 'www.madeupaddress.com', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('Camera Trap Metadata Standard', 'open data standard for storing and sharing camera trap data', 'https://bdj.pensoft.net/article/10197/', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO metadataStandards (name, description, uri, createdById, created, modifiedById, modified) VALUES ('CS3DP', 'Creation and use of 3D applications and data in research over the last decade leading has exploded, but at the same time, there has been little available guidance regarding the preservation of 3D digital objects and associated information in perpetuity. S', 'https://cs3dp.org/', @default_super_id, NOW(), @default_admin_id, NOW()); -- ===================================================================== -- REPOSITORIES -- ===================================================================== -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('DRYAD', 'Dryad is an open data publishing platform and a community committed to the open availability and routine re-use of all research data. We publish data in any format and any discipline. All Dryad data undergoes a curation process and is published under a CC', 'https://www.re3data.org/repository/https://www.re3data.org/api/v1/repository/r3d100000044', 'https://datadryad.org/stash', '["FAIR", "biodiversity", "interdisciplinary", "scientific and medical publications"]', '["other"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('GitHub', 'GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. With the collaborative features of GitHub.com, our desktop and mobile apps, and Git', 'https://www.re3data.org/repository/https://www.re3data.org/api/v1/repository/r3d100010375', 'https://github.com', '["open source software", "social networking", "web-based hosting service"]', '["other"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Zenodo', 'ZENODO builds and operates a simple and innovative service that enables researchers, scientists, EU projects and institutions to share and showcase multidisciplinary research results (data and publications) that are not part of the existing institutional ', 'https://www.re3data.org/repository/https://www.re3data.org/api/v1/repository/r3d100010468', 'https://zenodo.org/', '["FAIR", "multidisciplinary"]', '["other"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('University of Opole Knowledge Base', 'The University of Opole Knowledge Base is the central institutional system for recording, archiving, and disseminating the scholarly, artistic, and educational outputs of the University of Opole community. It includes a repository that stores publications', 'https://www.re3data.org/repository/r3d100014686', 'https://repo.uni.opole.pl/', '["Academic publications", "Bibliometrics", "Data citation", "Doctoral theses", "EOSC", "FAIR principles", "Institutional repository", "Interoperability", "Metadata management", "Open access", "Open research data", "OpenAIRE", "OpenDOAR", "Persistent identifiers (DOI, ORCID)", "Research data repository", "Scholarly communication"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Patient-Centered Outcomes Data Repository', 'The Patient-Centered Outcomes Data Repository (PCODR) is where you can find, access, and examine data on how different treatments work, collected from studies funded by the Patient-Centered Outcomes Research Institute (PCORI). It\'s the only collection foc', 'https://www.re3data.org/repository/r3d100014684', 'https://www.icpsr.umich.edu/sites/pcodr', '["COVID-19", "clinical effectiveness research", "methods studies", "patient-centered"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Open-archeOcsean', 'Open-archeOcsean is a curated catalogue of open-source data sets regarding the archaeology of the Pacific and Southeast Asia regions.', 'https://www.re3data.org/repository/r3d100014682', 'https://analytics.huma-num.fr/Sebastien.Plutniak/open-archeocsean/', '["FAIR", "archaeology", "oceania", "pacific", "prehistory", "southeast Asia"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('NIAID Data Ecosystem Discovery Portal', 'The NIAID Data Ecosystem Discovery Portal is a centralized search hub for infectious and immune-mediated disease datasets and computational tools from over 70 sources. These include NIAID-funded repositories as well as globally-relevant infectious and imm', 'https://www.re3data.org/repository/r3d100014680', 'https://data.niaid.nih.gov', '["FAIR", "immune-mediated disease", "infectious disease", "metadata"]', '["governmental"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('IOWMETA', 'The purpose of the metadata information system IOWMETA is to provide a comprehensive catalogue and a central infrastructure hub for all kinds of distributed research data stored at the Leibniz Institute of Baltic Sea Research Warnemünde (IOW). IOWMETA is ', 'https://www.re3data.org/repository/r3d100014676', 'https://iowmeta.io-warnemuende.de/', '["GeoNetwork", "environmental studies", "georeferenced metadata", "geoscientific information", "oceanographics"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('TSpace: University of Toronto Research Repository', 'TSpace is a free and secure research repository established by University of Toronto Libraries to disseminate and preserve the scholarly record of University of Toronto.', 'https://www.re3data.org/repository/r3d100014675', 'https://utoronto.scholaris.ca/', '["multidisciplinary", "open access", "theses and dissertations"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Marine Data Exchange', 'The Marine Data Exchange (MDE) is the first of its kind and a world leading digital platform of industry survey data, research and evidence that was created by The Crown Estate in 2013. It provides a digital platform for offshore industries to share surv', 'https://www.re3data.org/repository/r3d100014674', 'https://www.marinedataexchange.co.uk/', '["marine data"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Researchdata.se', 'Researchdata.se is a national web portal where you can find, share, and reuse research data from a wide range of disciplines. The portal focuses on searchability and access to data, making it easy to navigate thousands of datasets to find what you are loo', 'https://www.re3data.org/repository/r3d100014673', 'https://researchdata.se/en', '["FAIR", "multidisciplinary"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Research Data Centre of the Leibniz Institute of Ecological Urban and Regional Development', 'The Research Data Centre of the Leibniz Institute of Ecological Urban and Regional Development (IOER) provides high-resolution data, methods, indicators, models, tools and scenarios for cross-disciplinary, spatial sustainability research. The IOER RDC foc', 'https://www.re3data.org/repository/r3d100014379', 'https://data.fdz.ioer.de/', '["FAIR", "agriculture", "forest", "land use"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Research Data Universidad Simón Bolívar', 'Data Repository of the Universidad Simón Bolívar', 'https://www.re3data.org/repository/r3d100014241', 'https://dataverse.unisimon.edu.co', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('ELI ERIC Open Data Repository', 'The Extreme Light Infrastructure (ELI) is the world\'s most advanced laser-based research infrastructure. The ELI Facilities provide access to a broad range of world-class high-power, high repetition-rate laser systems and secondary sources. This enables c', 'https://www.re3data.org/repository/r3d100013889', 'https://data.eli-laser.eu/', '["FAIR", "laser", "spectrometry"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Maenduar', 'Maenduar in Tupi means "to remember". The Maenduar repository, created by LARHUD is an institutional repository (IBICT) dedicated to research data in Digital Humanities and Humanities. The repository encompasses the production of LARHUD members and partne', 'https://www.re3data.org/repository/r3d100013844', 'https://zenodo.org/communities/larhud/', '["digital humanities", "electoral studies"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Open-source Scientific Software and Service Repository', 'The ESCAPE Open-source Scientific Software and Service Repository (OSSR) is a sustainable open-access repository to share scientific software, services and datasets to the astro-particle-physics-related communities and enable open science. It is built as ', 'https://www.re3data.org/repository/r3d100013827', 'https://escape-ossr.gitlab.io/ossr-pages/', '["open source", "research software", "scientific software"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('GeneCorner Plasmid Collection', 'The BCCM/GeneCorner Plasmid Collection accepts plasmids from and distributes plasmids to researchers worldwide. Funding by the Belgian Science Policy (Belspo) allowed BCCM/GeneCorner to evolve into a unique plasmid repository in Europe.', 'https://www.re3data.org/repository/r3d100013667', 'https://bccm.belspo.be/about-us/bccm-genecorner', '["gene expression", "plasmid host strain", "plasmids"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('TU Data', 'TU Wien Research Data is an institutional repository of TU Wien to enable storing, sharing and publishing of digital objects, in particular research data. It facilitates the funders\' requirements for open access to research data and the FAIR principles by', 'https://www.re3data.org/repository/r3d100013557', 'https://researchdata.tuwien.at/', '["Code", "FAIR", "Interdisciplinary", "Research data"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Kikapu', '<<>>The University of the Western Cape (UWC) uses Figshare for Institutions for their institutional research data repository. It is called Kikapu, and serves as a repository for storing and disseminat', 'https://www.re3data.org/repository/r3d100013533', 'https://kikapu.uwc.ac.za/', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Center for Remote Sensing of Ice Sheets', 'The Center for Remote Sensing and Integrated Systems radar data repository containing data products from the Greenland Ice Sheet, the Antarctic Ice Sheet, sea ice, and land snow. (The former name is the Center for Remote Sensing of Ice Sheets.)', 'https://www.re3data.org/repository/r3d100013506', 'https://data.cresis.ku.edu/', '["frozen ground", "glaciers", "ice shelves", "sea ice", "soil moisture"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('E-depot of Erfgoed Leiden en Omstreken (part of Gemeente Leiden)', 'Erfgoed Leiden en Omstreken (ELO) is part of the municipality of Leiden. ELO performs services related to historical preservation, archaeology and archiving for the municipality of Leiden, as well as ten other surrounding municipalities and implementation', 'https://www.re3data.org/repository/r3d100014669', 'https://erfgoedleiden-e-depot.access.preservica.com/', '["building permits", "council meetings", "municipal archives", "private archives", "web archives", "zoning plans"]', '["governmental"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Repo4Cat', 'Repository for data, publications, and documentation of research from catalysis science.', 'https://www.re3data.org/repository/r3d100014668', 'https://repository.nfdi4cat.org/', '["nanoparticles", "propane dehydrogenation", "syngas"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('LTER-Italy Dataset Asset Registry', 'eLTER-RI is a pan-European in-situ research infrastructure whose mission is to study long-term ecological changes in terrestrial, freshwater and transitional ecosystems through a holistic “whole system” approach, based on the integration of different envi', 'https://www.re3data.org/repository/r3d100014665', 'https://dataregistry.lteritalia.it/', '["ERIC", "ESFRI", "Italy", "Long Term Ecological Research network", "Research Infrastructure"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Gaia Blu Cruise Inventory', 'This catalogue implements the Gaia Blu Cruise Inventory, which is the comprehensive catalogue of research objects generated during Gaia Blu cruises. It contributes to making Gaia Blu data FAIR (Findable, Accessible, Interoperable, and Reusable). Gaia Blu ', 'https://www.re3data.org/repository/r3d100014664', 'https://services.d4science.org/web/gaiablulab/cruise-inventory', '["FAIR", "Mediterranean Sea", "atmospheric sciences", "biology", "geology", "oceanography"]', '["disciplinary", "project-related"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Kasetsart University Knowledge Repository', 'Kasetsart University Knowledge Repository is the official institutional repository of Kasetsart University, designed to collect, preserve, and disseminate the scholarly output of the university community. It serves as a central platform for accessing a wi', 'https://www.re3data.org/repository/r3d100014663', 'https://kukr.lib.ku.ac.th/', '["agricultural science", "environmental science", "multidisciplinary"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('RMIT Research Repository', 'The Research Repository is a collection of peer reviewed and non-peer reviewed research outputs, publications, non-traditional research outputs, theses, datasets and open education resources produced by RMIT University researchers, including Higher Degree', 'https://www.re3data.org/repository/r3d100014662', 'https://research-repository.rmit.edu.au/', '["creative Works", "higher degree by research theses", "multidisciplinary", "publications"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('University of Johannesburg Data Repository', 'UJ DR is the University of Johannesburg’s Open Access Data Repository. Our data repository collects Research data/Raw data/Datasets, which are data in whatever formats or form collected, observed, generated, created and obtained during the entire course o', 'https://www.re3data.org/repository/r3d100014661', 'https://repository.uj.ac.za/research-data', '["Interdisciplinary", "Open Access"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('ODISSEI Portal', 'The ODISSEI Portal combines metadata from a wide variety of social sciences research data repositories into a single interface, allowing for advanced semantic queries to support findability, and facilitate data access. 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It is availabl', 'https://www.re3data.org/repository/r3d100014291', 'https://mediathek.hgk.fhnw.ch/amp/search', '["art education", "artistic research", "design research", "graphic design", "interior design", "performance art", "visual arts"]', '["disciplinary", "institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('CLOSER Discovery', 'CLOSER Discovery is a research tool for locating the variables that best suit your research interests and testing their robustness. 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It helps prevent data loss by storing it in a safe secure environment and enables your research data to b', 'https://www.re3data.org/repository/r3d100014218', 'https://researchdata.tees.ac.uk/research-data/', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Repositorio de datos de investigación de la Universidad del Pacífico', 'Repository of research data produced by the different departments and faculties of the Universidad del Pacífico', 'https://www.re3data.org/repository/r3d100014191', 'https://datasets.up.edu.pe/', '["accounting", "economics", "management", "social sciences"]', '["institutional"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('NCI Imaging Data Commons', 'NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure ', 'https://www.re3data.org/repository/r3d100014074', 'https://portal.imaging.datacommons.cancer.gov/', '["DICOM", "FAIR", "cancer imaging", "fluorescence", "pathology", "radiology"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Kadi4Mat', 'Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. 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It is currentl', 'https://www.re3data.org/repository/r3d100013817', 'http://renag.resif.fr/en', '["earth observation", "geodesy", "geophysics", "gravimetry"]', '["disciplinary"]', @default_super_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('protocols.io', 'A secure platform for developing and sharing reproducible methods. 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We publish data in any format and any discipline. All Dryad data undergoes a curation process and is published under a CC', 'https://www.re3data.org/repository/https://www.re3data.org/api/v1/repository/r3d100000044', 'https://datadryad.org/stash', '["FAIR", "biodiversity", "interdisciplinary", "scientific and medical publications"]', '["other"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('GitHub', 'GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. 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IOWMETA is ', 'https://www.re3data.org/repository/r3d100014676', 'https://iowmeta.io-warnemuende.de/', '["GeoNetwork", "environmental studies", "georeferenced metadata", "geoscientific information", "oceanographics"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('TSpace: University of Toronto Research Repository', 'TSpace is a free and secure research repository established by University of Toronto Libraries to disseminate and preserve the scholarly record of University of Toronto.', 'https://www.re3data.org/repository/r3d100014675', 'https://utoronto.scholaris.ca/', '["multidisciplinary", "open access", "theses and dissertations"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Marine Data Exchange', 'The Marine Data Exchange (MDE) is the first of its kind and a world leading digital platform of industry survey data, research and evidence that was created by The Crown Estate in 2013. 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The IOER RDC foc', 'https://www.re3data.org/repository/r3d100014379', 'https://data.fdz.ioer.de/', '["FAIR", "agriculture", "forest", "land use"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Research Data Universidad Simón Bolívar', 'Data Repository of the Universidad Simón Bolívar', 'https://www.re3data.org/repository/r3d100014241', 'https://dataverse.unisimon.edu.co', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('ELI ERIC Open Data Repository', 'The Extreme Light Infrastructure (ELI) is the world\'s most advanced laser-based research infrastructure. 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It is called Kikapu, and serves as a repository for storing and disseminat', 'https://www.re3data.org/repository/r3d100013533', 'https://kikapu.uwc.ac.za/', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Center for Remote Sensing of Ice Sheets', 'The Center for Remote Sensing and Integrated Systems radar data repository containing data products from the Greenland Ice Sheet, the Antarctic Ice Sheet, sea ice, and land snow. (The former name is the Center for Remote Sensing of Ice Sheets.)', 'https://www.re3data.org/repository/r3d100013506', 'https://data.cresis.ku.edu/', '["frozen ground", "glaciers", "ice shelves", "sea ice", "soil moisture"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('E-depot of Erfgoed Leiden en Omstreken (part of Gemeente Leiden)', 'Erfgoed Leiden en Omstreken (ELO) is part of the municipality of Leiden. ELO performs services related to historical preservation, archaeology and archiving for the municipality of Leiden, as well as ten other surrounding municipalities and implementation', 'https://www.re3data.org/repository/r3d100014669', 'https://erfgoedleiden-e-depot.access.preservica.com/', '["building permits", "council meetings", "municipal archives", "private archives", "web archives", "zoning plans"]', '["governmental"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Repo4Cat', 'Repository for data, publications, and documentation of research from catalysis science.', 'https://www.re3data.org/repository/r3d100014668', 'https://repository.nfdi4cat.org/', '["nanoparticles", "propane dehydrogenation", "syngas"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('LTER-Italy Dataset Asset Registry', 'eLTER-RI is a pan-European in-situ research infrastructure whose mission is to study long-term ecological changes in terrestrial, freshwater and transitional ecosystems through a holistic “whole system” approach, based on the integration of different envi', 'https://www.re3data.org/repository/r3d100014665', 'https://dataregistry.lteritalia.it/', '["ERIC", "ESFRI", "Italy", "Long Term Ecological Research network", "Research Infrastructure"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Gaia Blu Cruise Inventory', 'This catalogue implements the Gaia Blu Cruise Inventory, which is the comprehensive catalogue of research objects generated during Gaia Blu cruises. It contributes to making Gaia Blu data FAIR (Findable, Accessible, Interoperable, and Reusable). Gaia Blu ', 'https://www.re3data.org/repository/r3d100014664', 'https://services.d4science.org/web/gaiablulab/cruise-inventory', '["FAIR", "Mediterranean Sea", "atmospheric sciences", "biology", "geology", "oceanography"]', '["disciplinary", "project-related"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Kasetsart University Knowledge Repository', 'Kasetsart University Knowledge Repository is the official institutional repository of Kasetsart University, designed to collect, preserve, and disseminate the scholarly output of the university community. It serves as a central platform for accessing a wi', 'https://www.re3data.org/repository/r3d100014663', 'https://kukr.lib.ku.ac.th/', '["agricultural science", "environmental science", "multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('RMIT Research Repository', 'The Research Repository is a collection of peer reviewed and non-peer reviewed research outputs, publications, non-traditional research outputs, theses, datasets and open education resources produced by RMIT University researchers, including Higher Degree', 'https://www.re3data.org/repository/r3d100014662', 'https://research-repository.rmit.edu.au/', '["creative Works", "higher degree by research theses", "multidisciplinary", "publications"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('University of Johannesburg Data Repository', 'UJ DR is the University of Johannesburg’s Open Access Data Repository. Our data repository collects Research data/Raw data/Datasets, which are data in whatever formats or form collected, observed, generated, created and obtained during the entire course o', 'https://www.re3data.org/repository/r3d100014661', 'https://repository.uj.ac.za/research-data', '["Interdisciplinary", "Open Access"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('ODISSEI Portal', 'The ODISSEI Portal combines metadata from a wide variety of social sciences research data repositories into a single interface, allowing for advanced semantic queries to support findability, and facilitate data access. The Portal includes a link to the Da', 'https://www.re3data.org/repository/r3d100014660', 'https://portal.odissei.nl/', '["social sciences"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('PKRxiv', 'A managed open access data repository and visualization platform for collaborative sharing of anonymised, individual-level pharmacokinetic data, along with associated safety and efficacy data.', 'https://www.re3data.org/repository/r3d100014658', 'https://pkrxiv.org/', '["PBPK modelling", "pharmacodynamics", "pharmacokinetics", "population pharmacokinetics"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Tigray Regional Data Management Center for Health repository', 'The Tigray Regional Data Management Center for Health (RDMC), under the Tigray Health Research Institute (THRI), is a centralized hub for collecting, managing, and openly sharing regional health data. Its repository hosts a wealth of resources—including e', 'https://www.re3data.org/repository/r3d100014657', 'https://rdmcrepo.thri.gov.et', '["FAIR", "Tigray health", "ethiopia health", "health dataset", "health statistics data"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Blue-Cloud Resource Catalogue', 'Here you will find data, products, and resources of interest for the Blue-Cloud community. In particular, the Catalogue features datasets and products resulting from the Blue-Cloud Virtual Laboratories and the methods used to generate them.', 'https://www.re3data.org/repository/r3d100014656', 'https://blue-cloud.d4science.org/catalogue-bluecloud', '["fisheries data", "marine data", "marine environmental indicators", "phythoplankton", "zooplankton"]', '["project-related"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('DataverseLV', 'DataverseLV is a secure and sustainable repository for Latvian researchers to deposit, preserve, and share research data in line with Open Science and FAIR principles. The repository is developed, maintained, and curated by the Latvian Data Stewards Netwo', 'https://www.re3data.org/repository/r3d100014655', 'https://dv.dataverse.lv/', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Korea Social Science Data Archive', 'The Korea Social Science Data Archive (KOSSDA) is Korea’s leading archive for social science data. It collects, preserves, and provides access to diverse research materials such as surveys, interviews, and observation notes. KOSSDA builds digital database', 'https://www.re3data.org/repository/r3d100014654', 'https://kossda.snu.ac.kr/', '["FAIR", "cross-sectional study", "panel study", "qualitative data", "quantitative data", "social survey"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Mount Allison University Dataverse', 'The Mount Allison University Dataverse is a research data repository for our faculty, students, and staff. Files are stored in a secure environment on Canadian servers. Researchers can choose to make content available publicly, to specific individuals, or', 'https://www.re3data.org/repository/r3d100014631', 'https://borealisdata.ca/dataverse/mta', '["earth", "environment", "health", "medicine"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('IDB Open Data Catalog', 'Data Catalog that provides research and development data of demographics, migration, housing, poverty, inequality, education, employment, social security, health, among others for Latin America and the Caribbean.', 'https://www.re3data.org/repository/r3d100014409', 'https://data.iadb.org/', '["Caribbean", "Latin America", "development indicators", "multidisciplinary", "open data", "research data"]', '["other"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Research Data Centre of the Research Institute Social Cohesion', 'The Research Data Center of the Research Institute Social Cohesion (RDC-RISC) supports the scientific community by establishing a portal to available data relevant for empirical analysis on issues of social cohesion. This data portal includes data collect', 'https://www.re3data.org/repository/r3d100014378', 'https://fgz-risc-data.de/en/', '["cleavages", "cohesion", "conflict", "inequality", "networks", "polarization", "segregation"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('ISIMIP Repository', 'The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) is a community-driven climate impact modeling initiative that aims to contribute to a quantitative and cross-sectoral synthesis of the various impacts of climate change, including associate', 'https://www.re3data.org/repository/r3d100014370', 'https://data.isimip.org', '["climate impact science", "climate science"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Integrierter Katalog (InK) der Mediathek HGK Basel FHNW', 'The Integrated Catalogue (InK) of Mediathek of the Basel Academy of Art and Design (Hochschule für Gestaltung und Kunst Basel, HGK) hosts, collects, archives and makes available digital resources of HGK and its digital, special collections. It is availabl', 'https://www.re3data.org/repository/r3d100014291', 'https://mediathek.hgk.fhnw.ch/amp/search', '["art education", "artistic research", "design research", "graphic design", "interior design", "performance art", "visual arts"]', '["disciplinary", "institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('CLOSER Discovery', 'CLOSER Discovery is a research tool for locating the variables that best suit your research interests and testing their robustness. Metadata repository for Longitudinal Population Studies in the United Kingdom', 'https://www.re3data.org/repository/r3d100014274', 'https://discovery.closer.ac.uk', '["family", "physical health", "survey"]', '["multidisciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('UFS Figshare', 'figshare is the RDM system at the University. It is a cloud-based data repository that supports multiple file formats. Research data in the form of datasets, code, audio, images and more can be disseminated via the University\'s figshare. Citations can be ', 'https://www.re3data.org/repository/r3d100014256', 'https://ufs.figshare.com/', '["agriculture", "artificial intelligence", "earth sciences", "ecology", "economics", "food sciences", "veterinary"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('CESA | Repositorio de datos académicos', 'Discover the data on entrepreneurship projects, innovation plans, digital transformation proposals, consumers, and financial markets. Also, explore research on business, management, and entrepreneurship research development at our Business school.', 'https://www.re3data.org/repository/r3d100014254', 'https://opendata.cesa.edu.co/', '["Ccpital market", "FAIR", "Industry 4.0", "Python (Computer program language)", "R (Computer program language)", "behavioral operation", "business logistics", "emotional intelligence", "leadership", "organizational effectiveness", "portfolio management", "production management", "strategic planning", "technological innovations"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Arias Montano', 'Arias Montano, Institutional Repository of the University of Huelva is a repository of digital documents, whose aim is to publicize the scientific and teaching production of the University community, and ensure the preservation of their productions in dig', 'https://www.re3data.org/repository/r3d100014251', 'https://ariasmontano.uhu.es', '["multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Teesside University Research Data Repository', 'Teesside University Research Data Repository links to the University\'s Research Portal and enables your datasets to be linked to your staff profile. It helps prevent data loss by storing it in a safe secure environment and enables your research data to b', 'https://www.re3data.org/repository/r3d100014218', 'https://researchdata.tees.ac.uk/research-data/', '["FAIR", "multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Repositorio de datos de investigación de la Universidad del Pacífico', 'Repository of research data produced by the different departments and faculties of the Universidad del Pacífico', 'https://www.re3data.org/repository/r3d100014191', 'https://datasets.up.edu.pe/', '["accounting", "economics", "management", "social sciences"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('NCI Imaging Data Commons', 'NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure ', 'https://www.re3data.org/repository/r3d100014074', 'https://portal.imaging.datacommons.cancer.gov/', '["DICOM", "FAIR", "cancer imaging", "fluorescence", "pathology", "radiology"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Kadi4Mat', 'Kadi4Mat instance for use at the Karlsruhe Institute of Technology (KIT) and for cooperations, including the Cluster of Competence for Solid-state Batteries (FestBatt), the Battery Competence Cluster Analytics/Quality Assurance (AQua), and more. Kadi4Mat', 'https://www.re3data.org/repository/r3d100014008', 'https://kadi.iam.kit.edu/', '["FAIR", "electronic lab notebook", "high perfomance computing"]', '["disciplinary", "institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Redape', '\'Redape\' is a digital repository that aims to preserve and disseminate research data produced by the Brazilian Agricultural Research Corporation - Embrapa. It allows the organization, management and publication of data in accordance with the FAIR princip', 'https://www.re3data.org/repository/r3d100013980', 'https://www.redape.dados.embrapa.br/', '["FAIR", "agroecosystems, natural resources and environment", "animal production", "biomass, bioinputs and renewable energy", "biotechnology, nanotechnology, precision agriculture", "crop production", "economics, development and rural sociology", "food and human nutrition", "genetic resources", "organizational innovation"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Jean Paul – Sämtliche Briefe digital', 'The digital edition provides the complete correspondence of the German author Jean Paul (1763-1825) as well as some letters from contemporaries from his circle.', 'https://www.re3data.org/repository/r3d100013916', 'https://www.jeanpaul-edition.de/', '["correspondence", "digital edition", "romanticism", "scholarly edition"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('BORN Ontario', 'The Better Outcomes Registry & Network (BORN) is Ontario\'s prescribed perinatal, newborn and child registry with the role of facilitating quality care for families across the province. BORN collects, interprets, shares and rigorously protects high-quality', 'https://www.re3data.org/repository/r3d100013917', 'https://www.bornontario.ca/en/index.aspx', '["COVID-19", "health policy work", "performance measurement", "quality improvement", "surveillance"]', '["other"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Canadian Integrated Ocean Observing System Data Catalogue', 'The Canadian Integrated Ocean Observing System (CIOOS) Data Catalogue is an online open-access data catalogue designed for sharing reliable and high-quality. CIOOS is a collaboration between institutional, governmental, and non-governmental partners locat', 'https://www.re3data.org/repository/r3d100013914', 'https://catalogue.cioos.ca/', '["FAIR", "atmosphere", "coral", "essential ocean variable (EOV)", "fish", "meteorology", "microbe", "sea weather"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('RENAG-DC', 'Within the RESIF-EPOS observation research infrastructure and the Action Spécifique RESIF-GNSS action, the Reseau National GNSS permanent (RENAG) is the network of GNSS observation stations of French universities and research organizations. It is currentl', 'https://www.re3data.org/repository/r3d100013817', 'http://renag.resif.fr/en', '["earth observation", "geodesy", "geophysics", "gravimetry"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('protocols.io', 'A secure platform for developing and sharing reproducible methods. A research protocol is a document that describes the background, rationale, objectives, design, methodology, statistical considerations, and organization of a clinical research project.', 'https://www.re3data.org/repository/r3d100013705', 'https://www.protocols.io/', '["workflows"]', '["disciplinary"]', @default_super_id, NOW(), @default_admin_id, NOW()); +INSERT INTO repositories (name, description, uri, website, keywords, repositoryTypes, createdById, created, modifiedById, modified) VALUES ('Middlesex University Research Data Repository', 'Research Data Repository for Middlesex University, London, UK', 'https://www.re3data.org/repository/r3d100013660', 'https://mdx.figshare.com/', '["multidisciplinary"]', '["institutional"]', @default_super_id, NOW(), @default_admin_id, NOW()); -- Enable foreign key checks SET FOREIGN_KEY_CHECKS = 1; diff --git a/data-migrations/local-only/2025-11-20-0349-seed-affiliations.sql b/data-migrations/local-only/2025-11-20-0349-seed-affiliations.sql index 6b97d6dd..272fe668 100644 --- a/data-migrations/local-only/2025-11-20-0349-seed-affiliations.sql +++ b/data-migrations/local-only/2025-11-20-0349-seed-affiliations.sql @@ -7,151 +7,151 @@ SET @default_super_id := (SELECT id FROM userEmails WHERE email = 'super@example SET @default_admin_id := (SELECT id FROM userEmails WHERE email = 'admin@example.com'); -- Default CDL Affiliation with departments -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03yrm5c26', 'ROR', 'California Digital Library', 'California Digital Library (cdlib.org)', 'California Digital Library | cdlib.org | CDL ', 0, NULL, 'http://www.cdlib.org/', '["CDL"]', '[]', '["Archive"]', NULL, 'UC3 Helpdesk', 'uc3@cdlib.org', NULL, false, '
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"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["info@dcc.ac.uk"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01k9d6864', 'ROR', 'Digital Curation Centre', 'Digital Curation Centre (dcc.ac.uk)', 'Digital Curation Centre | dcc.ac.uk | DCC ', 1, NULL, 'http://www.dcc.ac.uk/', '["DCC"]', '[]', '["Other"]', NULL, 'DCC', 'info@dcc.ac.uk', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["info@dcc.ac.uk"]', true, @default_super_id, NOW(), @default_super_id, NOW()); -- Other affiliations -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0153tk833', 'ROR', 'University of Virginia', 'University of Virginia (virginia.edu)', 'University of Virginia | virginia.edu | UVA ', 1, '100008457', 'http://www.virginia.edu/', '["UVA"]', '[]', '["Education"]', NULL, 'Data Management Consulting Group', 'dmconsult@virginia.edu', 'urn:mace:incommon:virginia.edu', true, 'The Research Data Management librarian from the University of Virginia Library will respond to your request within 48 hours. If you have questions pertaining to this action please consult us at dmconsult@virginia.edu.
', '["dmconsult@virginia.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0168r3w48', 'ROR', 'University of California, San Diego', 'University of California, San Diego (ucsd.edu)', 'University of California, San Diego | ucsd.edu | UCSD UC San Diego', 1, '100007911', 'http://ucsd.edu/', '["UCSD"]', '["UC San Diego"]', '["Education"]',NULL,'The Library - Research Data Curation Program', 'Research-Data-Curation@ucsd.edu', 'urn:mace:incommon:ucsd.edu', true, 'The Research Data Curation Program from the University of California, San Diego Library will respond to your request. If you have questions pertaining to this action please contact us at Research-Data-Curation@ucsd.edu
', '["Research-Data-Curation@ucsd.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01pp8nd67', 'ROR', 'Smithsonian Institution', 'Smithsonian Institution (si.edu)', 'Smithsonian Institution | si.edu | SI ', 1, '100000014', 'http://www.si.edu/', '["SI"]', '[]', '["Government"]', NULL, 'Research Data Management at SI', 'SI-RDM@si.edu', 'https://idp.si.edu/idp/shibboleth', true, 'Feedback/questions on using DMPTool can be directed to SI-RDM@si.edu
', '["SI-RDM@si.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/047426m28', 'ROR', 'University of Illinois Urbana-Champaign', 'University of Illinois Urbana-Champaign (illinois.edu)', 'University of Illinois Urbana-Champaign | illinois.edu | UIUC University of Illinois', 1, '100005302', 'http://illinois.edu/', '["UIUC"]', '["University of Illinois"]', '["Education"]',NULL,'UIUC Research Data Service', 'researchdata@library.illinois.edu', 'urn:mace:incommon:uiuc.edu', true, 'Hello %{user_name}.
If you would like staff from the Research Data Service at University of Illinois at Urbana-Champaign (UIUC) to review your DMP, please click the "Request Feedback" button below. We will respond to your request within 48 hours, if not sooner.
If you need a review urgently, please email us directly at researchdata@library.illinois.edu with the deadline for submission to UIUC\'s Sponsored Project Administration (SPA), a link to the funding announcement, and your draft DMP.
Sincerely,
RDS Staff
', '["researchdata@library.illinois.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01an7q238', 'ROR', 'University of California, Berkeley', 'University of California, Berkeley (berkeley.edu)', 'University of California, Berkeley | berkeley.edu | UCB UC Berkeley', 1, '100006978', 'http://www.berkeley.edu/', '["UCB"]', '["UC Berkeley"]', '["Education"]',NULL,'Anna Sackmann', 'asackmann@berkeley.edu', 'urn:mace:incommon:berkeley.edu', false, 'Dear %
"%
Please email %
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dataserv@ucdavis.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04gyf1771', 'ROR', 'University of California, Irvine', 'University of California, Irvine (uci.edu)', 'University of California, Irvine | uci.edu | UCI UC Irvine', 1, '100008476', 'http://uci.edu/', '["UCI"]', '["UC Irvine"]', '["Education"]',NULL,'Digital Scholarship Services', 'libdss@uci.edu', 'urn:mace:incommon:uci.edu', true, 'A data librarian from University of California, Irvine (UCI) will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at libdss@uci.edu.
', '["libdss@uci.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/046rm7j60', 'ROR', 'University of California, Los Angeles', 'University of California, Los Angeles (ucla.edu)', 'University of California, Los Angeles | ucla.edu | UCLA State Normal School at Los Angeles | University of California Southern Branch | University of California at Los Angeles', 1, '100007185', 'http://www.ucla.edu/', '["UCLA"]', '["State Normal School at Los Angeles","University of California Southern Branch","University of California at Los Angeles"]', '["Education"]',NULL,'UCLA Library Data Management Group', 'data@library.ucla.edu', 'urn:mace:incommon:ucla.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@library.ucla.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00d9ah105', 'ROR', 'University of California, Merced', 'University of California, Merced (ucmerced.edu)', 'University of California, Merced | ucmerced.edu | UCM UC Merced', 1, '100010945', 'http://www.ucmerced.edu/', '["UCM"]', '["UC Merced"]', '["Education"]',NULL,'UC Merced Data Curation', 'curation@ucmerced.edu', 'urn:mace:incommon:ucmerced.edu', true, 'Hello %{user_name},
Your plan "%{plan_name} has been submitted for feedback from the Digital Curation and Scholarship unit of the UC Merced Library. If you have questions about this or would like additional follow-up on this plan, please contact us at curation@ucmerced.edu.
', '["curation@ucmerced.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03nawhv43', 'ROR', 'University of California, Riverside', 'University of California, Riverside (ucr.edu)', 'University of California, Riverside | ucr.edu | UCR UC Riverside', 1, '100007602', 'http://www.ucr.edu/', '["UCR"]', '["UC Riverside"]', '["Education"]',NULL,'UCR Library Data Consultation', 'dataconsult-lib@ucr.edu', 'urn:mace:incommon:ucr.edu', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at your organisation. If you have questions pertaining to this action, please contact us at %{organisation_email}.
', '["dataconsult-lib@ucr.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/043mz5j54', 'ROR', 'University of California, San Francisco', 'University of California, San Francisco (ucsf.edu)', 'University of California, San Francisco | ucsf.edu | UCSF ', 1, '100008069', 'https://www.ucsf.edu/', '["UCSF"]', '[]', '["Education"]',NULL,'Ariel Deardorff', 'ariel.deardorff@ucsf.edu', 'urn:mace:incommon:ucsf.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ariel.deardorff@ucsf.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02t274463', 'ROR', 'University of California, Santa Barbara', 'University of California, Santa Barbara (ucsb.edu)', 'University of California, Santa Barbara | ucsb.edu | UCSB UC Santa Barbara', 1, '100007183', 'http://www.ucsb.edu/', '["UCSB"]', '["UC Santa Barbara"]', '["Education"]',NULL,'Email', 'rds@library.ucsb.edu', 'urn:mace:incommon:ucsb.edu', true, 'A data specialist from University of California, Santa Barbara (UCSB) will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at rds@library.ucsb.edu
', '["rds@library.ucsb.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03s65by71', 'ROR', 'University of California, Santa Cruz', 'University of California, Santa Cruz (ucsc.edu)', 'University of California, Santa Cruz | ucsc.edu | UCSC UC Santa Cruz', 1, '100006358', 'http://www.ucsc.edu/', '["UCSC"]', '["UC Santa Cruz"]', '["Education"]',NULL,'Contact a UCSC Librarian', 'research@library.ucsc.edu', 'urn:mace:incommon:ucsc.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["research@library.ucsc.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00pjdza24', 'ROR', 'University of California System', 'University of California System (universityofcalifornia.edu)', 'University of California System | universityofcalifornia.edu | UC ', 1, '100005595', 'http://www.universityofcalifornia.edu/', '["UC"]', '[]', '["Education"]',NULL,'UC3 Helpdesk', 'dmptool@ucop.edu', 'urn:mace:incommon:ucop.edu', true, 'Someone from the University of California Curation Center (UC3) will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at uc3@ucop.edu
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/024mw5h28', 'ROR', 'University of Chicago', 'University of Chicago (uchicago.edu)', 'University of Chicago | uchicago.edu | UC UChicago', 1, '100007234', 'http://www.uchicago.edu/', '["UC"]', '["UChicago"]', '["Education"]',NULL,'Library Data Services', 'data-help@uchicago.edu', 'urn:mace:incommon:uchicago.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data-help@uchicago.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/020yh1f96', 'ROR', 'Ohio State University Hospital', 'Ohio State University Hospital (wexnermedical.osu.edu)', 'Ohio State University Hospital | wexnermedical.osu.edu | ', 0, NULL, 'https://wexnermedical.osu.edu/locations-and-parking/university-hospital', '[]', '[]', '["Healthcare"]',NULL,'Data Management Services', 'datamanagement@osu.edu', 'urn:mace:incommon:osu.edu', true, 'Hello %{user_name},
Your plan has been submitted for feedback to the Data Management Services team at The Ohio State University Libraries. You should expect a response within 7 business days. If you have questions about your submission, please contact us at datamanagement@osu.edu.
', '["datamanagement@osu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00jmfr291', 'ROR', 'University of Michigan–Ann Arbor', 'University of Michigan–Ann Arbor (umich.edu)', 'University of Michigan–Ann Arbor | umich.edu | UM UMich', 1, '100007270', 'https://www.umich.edu/', '["UM"]', '["UMich"]', '["Education"]',NULL,'Research Data Services', 'researchdataservices@umich.edu', 'https://shibboleth.umich.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdataservices@umich.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/043mer456', 'ROR', 'University of Nebraska–Lincoln', 'University of Nebraska–Lincoln (unl.edu)', 'University of Nebraska–Lincoln | unl.edu | UNL | NU ', 1, '100008114', 'http://www.unl.edu/', '["UNL ","NU"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shib.unl.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03efmqc40', 'ROR', 'Arizona State University', 'Arizona State University (asu.edu)', 'Arizona State University | asu.edu | ASU ', 1, '100007482', 'http://www.asu.edu/', '["ASU"]', '[]', '["Education"]',NULL,'Contact ASU Library Researcher Support', 'researchsupport@asu.edu', 'urn:mace:incommon:asu.edu', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from a research librarian at the ASU Library. Please allow 48 hours Monday through Friday for someone to respond to your request.
If you have questions pertaining to this action, please contact us or visit the ASU Library Researcher Support for more information on project support.
Thank you,
ASU Library
Research and Publication Services
Arizona State University
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/000e0be47', 'ROR', 'Northwestern University', 'Northwestern University (northwestern.edu)', 'Northwestern University | northwestern.edu | NU ', 1, '100007059', 'http://www.northwestern.edu/', '["NU"]', '[]', '["Education"]',NULL,'eResearch at Northwestern University', 'e-research@northwestern.edu', 'urn:mace:incommon:northwestern.edu', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback. A data librarian from Northwestern University Libraries (NU) will respond to your request within 48 hours. If you have any questions please contact us at e-reserach@northwestern.edu.
', '["e-research@northwestern.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0130frc33', 'ROR', 'University of North Carolina at Chapel Hill', 'University of North Carolina at Chapel Hill (unc.edu)', 'University of North Carolina at Chapel Hill | unc.edu | UNC UNC-Chapel Hill', 1, '100007890', 'http://www.unc.edu/', '["UNC"]', '["UNC-Chapel Hill"]', '["Education"]',NULL,'The University of North Carolina at Chapel Hill', 'odumarchive@unc.edu', 'urn:mace:incommon:unc.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["odumarchive@unc.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05hs6h993', 'ROR', 'Michigan State University', 'Michigan State University (msu.edu)', 'Michigan State University | msu.edu | MSU ', 1, '100007709', 'https://msu.edu/', '["MSU"]', '[]', '["Education"]',NULL,'Ranti Junus', 'junus@msu.edu', 'urn:mace:incommon:msu.edu', true, 'A data librarian from MSU Libraries will respond to your request within 2 business days. If you have questions or would like to follow up, please contact Scout Calvert, calvert4@msu.edu.
', '["junus@msu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04p491231', 'ROR', 'Pennsylvania State University', 'Pennsylvania State University (psu.edu)', 'Pennsylvania State University | psu.edu | PSU Penn State', 1, '100008321', 'http://www.psu.edu/', '["PSU"]', '["Penn State"]', '["Education"]',NULL,'Briana Wham', 'bde125@psu.edu', 'urn:mace:incommon:psu.edu', true, 'Dear %{user_name},
"%{plan_name}" has been sent to your DMPtool account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["bde125@psu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02mpq6x41', 'ROR', 'University of Illinois at Chicago', 'University of Illinois at Chicago (uic.edu)', 'University of Illinois at Chicago | uic.edu | UIC ', 1, '100008522', 'http://www.uic.edu/uic/', '["UIC"]', '[]', '["Education"]',NULL,'UIC DMP help', 'lib-data@uic.edu', 'https://shibboleth.uic.edu/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["lib-data@uic.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/020qm1538', 'ROR', 'California State University System', 'California State University System (calstate.edu)', 'California State University System | calstate.edu | CSU Cal State', 0, NULL, 'http://www.calstate.edu/', '["CSU"]', '["Cal State"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp-co.calstate.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01c8f2y33', 'ROR', 'Moss Landing Marine Laboratories', 'Moss Landing Marine Laboratories (mlml.calstate.edu)', 'Moss Landing Marine Laboratories | mlml.calstate.edu | MLML ', 1, NULL, 'https://www.mlml.calstate.edu/', '["MLML"]', '[]', '["Facility"]',NULL,'Katie Lage, Librarian MLML/MBARI Research Library', 'klage@mlml.calstate.edu', 'urn:mace:incommon:mlml.calstate.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["klage@mlml.calstate.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0294hxs80', 'ROR', 'California State University Los Angeles', 'California State University Los Angeles (calstatela.edu)', 'California State University Los Angeles | calstatela.edu | CSULA Cal State LA', 0, NULL, 'http://www.calstatela.edu/', '["CSULA"]', '["Cal State LA"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idpp.calstatela.edu/idp', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03enmdz06', 'ROR', 'California State University, Fresno', 'California State University, Fresno (fresnostate.edu)', 'California State University, Fresno | fresnostate.edu | Fresno State University', 1, '100010075', 'http://www.fresnostate.edu/', '[]', '["Fresno State University"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shib-idp.its.csufresno.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00hj54h04', 'ROR', 'The University of Texas at Austin', 'The University of Texas at Austin (utexas.edu)', 'The University of Texas at Austin | utexas.edu | UT Austin', 1, '100008562', 'http://www.utexas.edu/', '[]', '["UT Austin"]', '["Education"]',NULL,'Meryl Brodsky', 'Meryl.Brodsky@austin.utexas.edu', 'https://enterprise.login.utexas.edu/idp/shibboleth', false, 'The Research Data Services unit at UT Libraries will respond to your request within 48 hours. If you have any questions about this or need more urgent attention, please contact j.trelogan@austin.utexas.edu.
', '["Meryl.Brodsky@austin.utexas.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04tj63d06', 'ROR', 'North Carolina State University', 'North Carolina State University (ncsu.edu)', 'North Carolina State University | ncsu.edu | NCSU ', 1, '100007703', 'https://www.ncsu.edu/', '["NCSU"]', '[]', '["Education"]',NULL,'NCSU Data Management Planning', 'library_datamanagement@ncsu.edu', 'urn:mace:incommon:ncsu.edu', true, '
Hi %{user_name},
Your plan "%{plan_name}" has been submitted for feedback from a librarian at NC State. We will review your draft DMP and get back to you within 5 business days. If you have any questions or need us to expedite our feedback to you, please contact us at library_datamanagement@ncsu.edu.
Thanks!
', '["library_datamanagement@ncsu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00za53h95', 'ROR', 'Johns Hopkins University', 'Johns Hopkins University (jhu.edu)', 'Johns Hopkins University | jhu.edu | JHU ', 1, '100007880', 'https://www.jhu.edu/', '["JHU"]', '[]', '["Education"]',NULL,'Contact for feedback on your plan and to archive your data in the JHU Data Archive', 'dataservices@jhu.edu', 'urn:mace:incommon:johnshopkins.edu', true, '
Your draft data management plan (DMP) has been sent to JHU Data Services. One of our consultants will provide feedback on your DMP within 2 business days.
Thank you,
JHU Data Services
(https://dataservices.library.jhu.edu/)
dataservices@jhu.edu
', '["dataservices@jhu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/008zs3103', 'ROR', 'Rice University', 'Rice University (rice.edu)', 'Rice University | rice.edu | William Marsh Rice University', 1, '100007863', 'http://www.rice.edu/', '[]', '["William Marsh Rice University"]', '["Education"]',NULL,'Lisa Spiro (Fondren Library)', ' reasearchdata@rice.edu', 'https://idp.rice.edu/idp/shibboleth', false, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at your organisation. If you have questions pertaining to this action, please contact us at %{organisation_email}.
', '[" reasearchdata@rice.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03m2x1q45', 'ROR', 'University of Arizona', 'University of Arizona (arizona.edu)', 'University of Arizona | arizona.edu | UA ', 1, '100007899', 'http://www.arizona.edu/', '["UA"]', '[]', '["Education"]',NULL,'Data Management Services Team', 'data-management@arizona.edu', 'urn:mace:incommon:arizona.edu', true, 'A specialist from University of Arizona will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at data-management@arizona.edu.
', '["data-management@arizona.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04zjtrb98', 'ROR', 'Old Dominion University', 'Old Dominion University (odu.edu)', 'Old Dominion University | odu.edu | ODU ', 1, '100009980', 'http://www.odu.edu/#prospective', '["ODU"]', '[]', '["Education"]',NULL,'Creating a Data Management Plan at ODU', 'swen@odu.edu', 'urn:mace:incommon:odu.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["swen@odu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02qt0xs84', 'ROR', 'Humboldt State University', 'Humboldt State University (humboldt.edu)', 'Humboldt State University | humboldt.edu | HSU ', 1, '100008121', 'http://www.humboldt.edu/', '["HSU"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:humboldt.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04t5xt781', 'ROR', 'Northeastern University', 'Northeastern University (northeastern.edu)', 'Northeastern University | northeastern.edu | NU | NEU ', 0, NULL, 'http://www.northeastern.edu/', '["NU","NEU"]', '[]', '["Education"]',NULL,'Contact Data Management at Northeastern', 'j.ferguson@northeastern.edu', 'https://neuidmsso.neu.edu/idp/shibboleth', true, 'Hello %{user_name},
Your data management plan "%{plan_name}" has been submitted for feedback from an administrator at your organization. Please allow 2 business days for us to respond with feedback.
If you have questions pertaining to this action, please contact us.
', '["j.ferguson@northeastern.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03v76x132', 'ROR', 'Yale University', 'Yale University (yale.edu)', 'Yale University | yale.edu | Collegiate School | Yale College', 1, '100005326', 'http://www.yale.edu', '[]', '["Collegiate School","Yale College"]', '["Education"]',NULL,'Yale DMPTool Administrator', 'barbara.esty@yale.edu', 'https://auth.yale.edu/idp/shibboleth', false, '
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["barbara.esty@yale.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02dgjyy92', 'ROR', 'University of Miami', 'University of Miami (miami.edu)', 'University of Miami | miami.edu | UM | U Miami ', 1, '100006686', 'http://www.miami.edu/', '["UM","U Miami"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://caneid.miami.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/027bzz146', 'ROR', 'California State University, Chico', 'California State University, Chico (csuchico.edu)', 'California State University, Chico | csuchico.edu | CSUC Chico State', 1, '100009972', 'http://www.csuchico.edu/', '["CSUC"]', '["Chico State"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shibboleth.csuchico.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02jqj7156', 'ROR', 'George Mason University', 'George Mason University (gmu.edu)', 'George Mason University | gmu.edu | ', 1, '100006369', 'https://www.gmu.edu/', '[]', '[]', '["Education"]',NULL,'Data Management Help', 'datahelp@gmu.edu', 'https://shibboleth.gmu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["datahelp@gmu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03hbp5t65', 'ROR', 'University of Idaho', 'University of Idaho (uidaho.edu)', 'University of Idaho | uidaho.edu | UI ', 0, NULL, 'http://www.uidaho.edu/', '["UI"]', '[]', '["Education"]',NULL,'U-Idaho Library', 'jkenyon@uidaho.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jkenyon@uidaho.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/028pmsz77', 'ROR', 'James Madison University', 'James Madison University (jmu.edu)', 'James Madison University | jmu.edu | JMU ', 1, '100008289', 'http://www.jmu.edu/', '["JMU"]', '[]', '["Education"]',NULL,'Head of Scholarly Communications Strategies', 'shorisyl@jmu.edu', 'urn:mace:incommon:jmu.edu', true, 'A librarian from James Madison University (JMU) will respond to your request within 48 hours. If you have questions pertaining to this action please contact shorisyl@jmu.edu.
', '["shorisyl@jmu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05by5hm18', 'ROR', 'California State Polytechnic University', 'California State Polytechnic University (cpp.edu)', 'California State Polytechnic University | cpp.edu | CPP Cal Poly Pomona | Cal Poly', 1, '100008508', 'http://www.cpp.edu/', '["CPP"]', '["Cal Poly Pomona","Cal Poly"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.calpoly.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00mkhxb43', 'ROR', 'University of Notre Dame', 'University of Notre Dame (nd.edu)', 'University of Notre Dame | nd.edu | ', 1, '100008109', 'https://www.nd.edu/', '[]', '[]', '["Education"]',NULL,'cds@nd.edu for DMP help.', 'cds@nd.edu', 'https://login.nd.edu/idp/shibboleth', true, 'Please contact Research Data Services <hl-research-data-services-list@nd.edu> for expert feedback, and check this online resource for ND DMP tips.
', '["cds@nd.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05p8z3f47', 'ROR', 'Purdue University System', 'Purdue University System (purdue.edu)', 'Purdue University System | purdue.edu | ', 0, NULL, 'http://www.purdue.edu/', '[]', '[]', '["Education"]',NULL,'Purdue Libraries Research Data - for help with data management plans', 'researchdata@purdue.edu', 'https://idp.purdue.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdata@purdue.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05fs6jp91', 'ROR', 'University of New Mexico', 'University of New Mexico (unm.edu)', 'University of New Mexico | unm.edu | UNM Universitatis Novus Mexico', 1, '100007179', 'http://www.unm.edu/', '["UNM"]', '["Universitatis Novus Mexico"]', '["Education"]',NULL,'Data curation at University of New Mexico', 'rds@unm.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["rds@unm.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01zkghx44', 'ROR', 'Georgia Institute of Technology', 'Georgia Institute of Technology (gatech.edu)', 'Georgia Institute of Technology | gatech.edu | GT Georgia Tech', 1, '100006778', 'http://www.gatech.edu/', '["GT"]', '["Georgia Tech"]', '["Education"]',NULL,'Georgia Institute of Technology', 'susan.parham@gatech.edu', 'https://idp.gatech.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["susan.parham@gatech.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01f5ytq51', 'ROR', 'Texas A&M University', 'Texas A&M University (tamu.edu)', 'Texas A&M University | tamu.edu | TAMU ', 1, '100007904', 'https://www.tamu.edu/', '["TAMU"]', '[]', '["Education"]',NULL,'TAMU DMPTool Administrator', 'xuzhihong@tamu.edu', 'urn:mace:incommon:tamu.edu', true, 'A data librarian from Texas A&M University will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at xuzhihong@tamu.edu.
', '["xuzhihong@tamu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01y2jtd41', 'ROR', 'University of Wisconsin–Madison', 'University of Wisconsin–Madison (wisc.edu)', 'University of Wisconsin–Madison | wisc.edu | UW UW–Madison', 1, '100007015', 'http://www.wisc.edu/', '["UW"]', '["UW–Madison"]', '["Education"]',NULL,'Research Data Services', 'researchdata-working@lists.wisc.edu', 'https://login.wisc.edu/idp/shibboleth', true, 'An RDS Consultant from University of Wisconsin-Madison will be in touch about reviewing your DMP within two business days. If you have any questions pertaining to this action please contact us at researchdata-working@lists.wisc.edu. Thank you!
', '["researchdata-working@lists.wisc.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01kg8sb98', 'ROR', 'Indiana University', 'Indiana University (iu.edu)', 'Indiana University | iu.edu | IU ', 1, '100006733', 'http://www.iu.edu/', '["IU"]', '[]', '["Education"]',NULL,'Indiana University', 'iuswdata@indiana.edu', 'https://idp.login.iu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["iuswdata@indiana.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05h9q1g27', 'ROR', 'Texas State University', 'Texas State University (txstate.edu)', 'Texas State University | txstate.edu | ', 0, NULL, 'http://www.txstate.edu/', '[]', '[]', '["Education"]',NULL,'TXST Data Contact', 'digitalcollections@txstate.edu', 'https://authentic.txstate.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["digitalcollections@txstate.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/037s24f05', 'ROR', 'Clemson University', 'Clemson University (clemson.edu)', 'Clemson University | clemson.edu | Clemson Agricultural College of South Carolina', 1, '100006498', 'http://www.clemson.edu/', '[]', '["Clemson Agricultural College of South Carolina"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:clemson.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00ysfqy60', 'ROR', 'Oregon State University', 'Oregon State University (oregonstate.edu)', 'Oregon State University | oregonstate.edu | OSU ', 1, '100009612', 'http://oregonstate.edu/', '["OSU"]', '[]', '["Education"]',NULL,'OSU Research Data Services', 'ResearchDataServices@oregonstate.edu', 'https://login.oregonstate.edu/idp/shibboleth', true, 'Your plan will be reviewed by Research Data Services at Oregon State University. Please allow 48 hours for someone to respond to your request. If you have questions or comments about the process you can e-mail ResearchDataServices@oregonstate.edu. If you have an upcoming deadline (sooner than a week) please let us know by writing an e-mail to ResearchDataServices@oregonstate.edu.
', '["ResearchDataServices@oregonstate.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/052w4zt36', 'ROR', 'American University', 'American University (american.edu)', 'American University | american.edu | AU ', 1, '100010690', 'http://www.american.edu/', '["AU"]', '[]', '["Education"]',NULL,'Stefan Kramer', 'skramer@american.edu', 'https://idp.american.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["skramer@american.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04rswrd78', 'ROR', 'Iowa State University', 'Iowa State University (iastate.edu)', 'Iowa State University | iastate.edu | ISU Iowa State', 1, '100009227', 'http://www.iastate.edu/', '["ISU"]', '["Iowa State"]', '["Education"]',NULL,'Research Data Services - Univ. Library', 'datashare@iastate.edu', 'https://idp.iastate.edu/shibboleth', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback. We will be in touch with you within 48 hours or less but may need more time to review your plan.
If you have questions please contact us at datashare@iastate.edu
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@tulane.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03tzaeb71', 'ROR', 'University of Hawaii System', 'University of Hawaii System (hawaii.edu)', 'University of Hawaii System | hawaii.edu | UH University of Hawaii', 1, '100008782', 'http://www.hawaii.edu/', '["UH"]', '["University of Hawaii"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.hawaii.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02k3smh20', 'ROR', 'University of Kentucky', 'University of Kentucky (uky.edu)', 'University of Kentucky | uky.edu | ', 1, '100007472', 'http://www.uky.edu/', '[]', '[]', '["Education"]',NULL,'Adrian Ho', 'adrian.ho@uky.edu', 'https://ukidp.uky.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["adrian.ho@uky.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01j8e0j24', 'ROR', 'California State University, San Marcos', 'California State University, San Marcos (csusm.edu)', 'California State University, San Marcos | csusm.edu | CSUSM Cal State San Marcos', 1, '100007789', 'http://www.csusm.edu/', '["CSUSM"]', '["Cal State San Marcos"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.csusm.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00yn2fy02', 'ROR', 'Portland State University', 'Portland State University (pdx.edu)', 'Portland State University | pdx.edu | PSU ', 1, '100007083', 'https://www.pdx.edu/', '["PSU"]', '[]', '["Education"]',NULL,'Portland State University', 'lib-data-management@pdx.edu', 'https://sso.pdx.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["lib-data-management@pdx.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/017zqws13', 'ROR', 'University of Minnesota', 'University of Minnesota (twin-cities.umn.edu)', 'University of Minnesota | twin-cities.umn.edu | University of Minnesota, Twin Cities', 1, '100007913', 'http://twin-cities.umn.edu/', '[]', '["University of Minnesota, Twin Cities"]', '["Education"]',NULL,'University of Minnesota--Twin Cities', 'ljohnsto@umn.edu', 'urn:mace:incommon:umn.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ljohnsto@umn.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/031q21x57', 'ROR', 'University of Wisconsin–Milwaukee', 'University of Wisconsin–Milwaukee (www4.uwm.edu)', 'University of Wisconsin–Milwaukee | www4.uwm.edu | UWM UW–Milwaukee', 1, '100006817', 'http://www4.uwm.edu/', '["UWM"]', '["UW–Milwaukee"]', '["Education"]',NULL,'Kristin Briney, Data Services Librarian', 'briney@uwm.edu', 'https://idp.uwm.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["briney@uwm.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00v97ad02', 'ROR', 'University of North Texas', 'University of North Texas (unt.edu)', 'University of North Texas | unt.edu | UNT ', 1, '100008973', 'http://www.unt.edu/', '["UNT"]', '[]', '["Education"]',NULL,'Research Data Management Support', 'John.Martin@unt.edu', 'https://sso.unt.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["John.Martin@unt.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03r0ha626', 'ROR', 'University of Utah', 'University of Utah (utah.edu)', 'University of Utah | utah.edu | UU University of Deseret', 1, '100007747', 'http://www.utah.edu/', '["UU"]', '["University of Deseret"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:utah.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03czfpz43', 'ROR', 'Emory University', 'Emory University (emory.edu)', 'Emory University | emory.edu | ', 1, '100006939', 'http://www.emory.edu/home/index.html', '[]', '[]', '["Education"]',NULL,'Emory Data Management Plan Help', 'dataplans@emory.edu', 'https://login.emory.edu/idp/shibboleth', true, 'A data librarian from Emory University will respond to your request within 48 hours. If you have questions about reviews of data management plans, please contact us at dataplans@emory.edu.
', '["dataplans@emory.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03qt6ba18', 'ROR', 'Georgia State University', 'Georgia State University (gsu.edu)', 'Georgia State University | gsu.edu | GSU ', 1, '100008545', 'http://www.gsu.edu/', '["GSU"]', '[]', '["Education"]',NULL,'Data management at Georgia State University', 'libdatahelp@gsu.edu', 'https://idp.gsu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["libdatahelp@gsu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04bdffz58', 'ROR', 'Drexel University', 'Drexel University (drexel.edu)', 'Drexel University | drexel.edu | Drexel Institute | Drexel Institute of Technology', 1, '100008211', 'http://www.drexel.edu/', '[]', '["Drexel Institute","Drexel Institute of Technology"]', '["Education"]',NULL,'Data management at Drexel University', 'datamanagement@drexel.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["datamanagement@drexel.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02smfhw86', 'ROR', 'Virginia Tech', 'Virginia Tech (vt.edu)', 'Virginia Tech | vt.edu | Virginia Polytechnic Institute and State University', 1, '100007263', 'https://www.vt.edu/about/index.html', '[]', '["Virginia Polytechnic Institute and State University"]', '["Education"]',NULL,'Data Consultants for Questions and DMP Review Requests: dataservices@vt.edu', 'dataservices@vt.edu', 'urn:mace:incommon:vt.edu', true, 'A data management consultant from Virginia Tech University Libraries will respond to your feedback request with 2 business days. If you have other research data management questions or need more timely assistance please contact us at dataservices@vt.edu.
', '["dataservices@vt.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00f54p054', 'ROR', 'Stanford University', 'Stanford University (stanford.edu)', 'Stanford University | stanford.edu | SU Leland Stanford Junior University', 1, '100005492', 'http://www.stanford.edu/', '["SU"]', '["Leland Stanford Junior University"]', '["Education"]',NULL,'Stanford Libraries Data Management Services', 'ask-data-services@lists.stanford.edu', 'urn:mace:incommon:stanford.edu', true, 'Hello %{user_name},
Your Data Management Plan ("%{plan_name}")has been submitted to the data management experts at Stanford Libraries for review. Someone will review your plan and provide you with feedback shortly. If you have questions pertaining to this or an urgent deadline for the review, please contact us at ask-data-services@lists.stanford.edu.
Thank you.
', '["ask-data-services@lists.stanford.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/83c32cc7', 'DMPTOOL', 'University of Alabama', 'University of Alabama', 'University of Alabama | guides.lib.ua.edu | ', 0, NULL, 'http://guides.lib.ua.edu/rdmp', '[]', '[]', '["Education"]',NULL,'University of Alabama E-Science', 'rdmphelp@listserv.ua.edu', 'https://idp.ua.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["rdmphelp@listserv.ua.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00cvxb145', 'ROR', 'University of Washington', 'University of Washington (washington.edu)', 'University of Washington | washington.edu | UW ', 1, '100007812', 'http://www.washington.edu/', '["UW"]', '[]', '["Education"]',NULL,'UW Research Data Services Librarian', 'jmuil@uw.edu', 'urn:mace:incommon:washington.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jmuil@uw.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02y3ad647', 'ROR', 'University of Florida', 'University of Florida (ufl.edu)', 'University of Florida | ufl.edu | UF University of the State of Florida', 1, '100007698', 'http://www.ufl.edu/', '["UF"]', '["University of the State of Florida"]', '["Education"]',NULL,'Research Data Management at UF', 'Datamgmt-L@lists.ufl.edu', 'https://login.ufl.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["Datamgmt-L@lists.ufl.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/025r5qe02', 'ROR', 'Syracuse University', 'Syracuse University (syr.edu)', 'Syracuse University | syr.edu | SU ', 1, '100007126', 'http://www.syr.edu/', '["SU"]', '[]', '["Education"]',NULL,'Research Data Services at SU', 'DataSvcs@syr.edu', 'https://shibidp.syr.edu/idp/shibboleth', true, 'A data librarian from Syracuse University will respond to your request as soon as possible. If you have questions pertaining to this action please contact us at DataSvcs@syr.edu.
', '["DataSvcs@syr.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/034mtvk83', 'ROR', 'University of New Orleans', 'University of New Orleans (uno.edu)', 'University of New Orleans | uno.edu | UNO ', 1, '100009723', 'http://www.uno.edu/', '["UNO"]', '[]', '["Education"]',NULL,'UNO Data management', 'dmp@uno.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmp@uno.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05bnh6r87', 'ROR', 'Cornell University', 'Cornell University (cornell.edu)', 'Cornell University | cornell.edu | CU ', 1, '100007231', 'http://www.cornell.edu/', '["CU"]', '[]', '["Education"]',NULL,'Cornell\'s Research Data Management Service Group (RDMSG)', 'rdmsg-help@cornell.edu', 'https://shibidp.cit.cornell.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["rdmsg-help@cornell.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0190ak572', 'ROR', 'New York University', 'New York University (nyu.edu)', 'New York University | nyu.edu | NYU ', 1, '100006732', 'http://www.nyu.edu/', '["NYU"]', '[]', '["Education"]',NULL,'DMP Help', 'data.services@nyu.edu', 'urn:mace:incommon:nyu.edu', true, 'Hello %{user_name}! Your plan, "%{plan_name}", has been sent to a data librarian at NYU Data Services who will respond to your request within 48 hours. If you have questions pertaining to this request please contact us at %{organisation_email}.
', '["data.services@nyu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/022kthw22', 'ROR', 'University of Rochester', 'University of Rochester (rochester.edu)', 'University of Rochester | rochester.edu | UR ', 1, '100008091', 'https://www.rochester.edu/', '["UR"]', '[]', '["Education"]',NULL,'University of Rochester Data Management', 's.pugachev@rochester.edu', 'https://shib2.its.rochester.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["s.pugachev@rochester.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05dk0ce17', 'ROR', 'Washington State University', 'Washington State University (wsu.edu)', 'Washington State University | wsu.edu | WSU ', 1, '100007588', 'https://wsu.edu/', '["WSU"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shibidp.wsu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02nkdxk79', 'ROR', 'Virginia Commonwealth University', 'Virginia Commonwealth University (vcu.edu)', 'Virginia Commonwealth University | vcu.edu | VCU ', 1, '100009238', 'http://www.vcu.edu/', '["VCU"]', '[]', '["Education"]',NULL,'VCU Libraries RDM Team', 'libdatahelp@vcu.edu', 'https://shibboleth.vcu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["libdatahelp@vcu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01yc7t268', 'ROR', 'Washington University in St. Louis', 'Washington University in St. Louis (wustl.edu)', 'Washington University in St. Louis | wustl.edu | WUSTL ', 1, '100007268', 'http://wustl.edu/', '["WUSTL"]', '[]', '["Education"]',NULL,'Jennifer Moore', 'j.moore@wustl.edu', 'https://login.wustl.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["j.moore@wustl.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00hx57361', 'ROR', 'Princeton University', 'Princeton University (princeton.edu)', 'Princeton University | princeton.edu | College of New Jersey', 1, '100006734', 'http://www.princeton.edu/main/', '[]', '["College of New Jersey"]', '["Education"]',NULL,'Princeton Research Data Service', 'prds@princeton.edu', 'https://idp.princeton.edu/idp/shibboleth', true, 'Hello %{user_name},
Thank you for submitting your plan for feedback. Please allow 24-48 hours for someone to respond to your request. Meanwhile, if you have any additional questions, please contact us at prds@princeton.edu, or feel free to schedule a consultation from our website: https://researchdata.princeton.edu. Thanks!
Best,
Princeton Research Data Service Team
', '["prds@princeton.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00ds41r10', 'ROR', 'Carnegie Mellon University Australia', 'Carnegie Mellon University Australia (australia.cmu.edu)', 'Carnegie Mellon University Australia | australia.cmu.edu | CMU ', 0, NULL, 'https://www.australia.cmu.edu/', '["CMU"]', '[]', '["Education"]',NULL,'Contact University Libraries Data Services for help with data management plans', 'data@cmu.libanswers.com', 'https://login.cmu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@cmu.libanswers.com"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02ttsq026', 'ROR', 'University of Colorado Boulder', 'University of Colorado Boulder (colorado.edu)', 'University of Colorado Boulder | colorado.edu | UCB CU-Boulder', 1, '100007493', 'http://www.colorado.edu/', '["UCB"]', '["CU-Boulder"]', '["Education"]',NULL,'Get Help at CU Boulder', 'crdds@colorado.edu', 'https://fedauth.colorado.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["crdds@colorado.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/ed51675d', 'DMPTOOL', 'Weill Cornell Medicine', 'Weill Cornell Medicine', 'Weill Cornell Medicine | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'WCM DMPTool Admin', 'drw2004@med.cornell.edu', 'https://login.weill.cornell.edu/idp', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["drw2004@med.cornell.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05qwgg493', 'ROR', 'Boston University', 'Boston University (bu.edu)', 'Boston University | bu.edu | BU Boston U', 1, '100007161', 'http://www.bu.edu/', '["BU"]', '["Boston U"]', '["Education"]',NULL,'BU Research Data Management', 'data@bu.edu', 'https://shib.bu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@bu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00kx1jb78', 'ROR', 'Temple University', 'Temple University (temple.edu)', 'Temple University | temple.edu | ', 1, '100005806', 'http://www.temple.edu/', '[]', '[]', '["Education"]',NULL,'Temple RDS', 'tul-rds@temple.edu', 'https://fim.temple.edu/idp/shibboleth', true, 'Dear %{user_name}, We received your request for feedback on your plan, %{plan_name} .
A librarian from Temple University will respond to your request within 3 business days. If you have questions pertaining to this action, please contact us at tul-rds@temple.edu.
Thank you.
', '["tul-rds@temple.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02e3zdp86', 'ROR', 'Boise State University', 'Boise State University (boisestate.edu)', 'Boise State University | boisestate.edu | BSU ', 1, '100007233', 'https://www.boisestate.edu/', '["BSU"]', '[]', '["Education"]',NULL,'Boise State Data Management Support', 'datamanagement@boisestate.edu', 'https://idp.boisestate.edu/idp/shibboleth', false, 'A data librarian from Boise State University will respond to your request within 2 business days. If you have questions pertaining to this action, pease contact us at datamanagement@boisestate.edu.
', '["datamanagement@boisestate.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05qghxh33', 'ROR', 'Stony Brook University', 'Stony Brook University (stonybrook.edu)', 'Stony Brook University | stonybrook.edu | SBU SUNY Stony Brook', 1, '100007259', 'http://www.stonybrook.edu/', '["SBU"]', '["SUNY Stony Brook"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:stonybrook.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/020f3ap87', 'ROR', 'University of Tennessee at Knoxville', 'University of Tennessee at Knoxville (utk.edu)', 'University of Tennessee at Knoxville | utk.edu | UTK | UT University of Tennessee', 1, '100008526', 'http://www.utk.edu/', '["UTK","UT"]', '["University of Tennessee"]', '["Education"]',NULL,'Contact the Data Services Team', 'dataservices@utk.edu', 'https://idp.utk.edu/idp/shibboleth', true, 'Thank you for submitting your data management plan through the DMPTool.
Your request for feedback has been submitted to the Data Services Team at the UT Libraries. Any feedback will be provided within 3 business days through the DMPTool.
If you have any questions in the meantime, please contact the Data Services Team at dataservices@utk.edu.
', '["dataservices@utk.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01g9vbr38', 'ROR', 'Oklahoma State University', 'Oklahoma State University (go.okstate.edu)', 'Oklahoma State University | go.okstate.edu | OSU Oklahoma State', 1, '100007808', 'http://go.okstate.edu/', '["OSU"]', '["Oklahoma State"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.okstate.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00py81415', 'ROR', 'Duke University', 'Duke University (duke.edu)', 'Duke University | duke.edu | ', 1, '100006510', 'http://www.duke.edu/', '[]', '[]', '["Education"]',NULL,'Duke University Libraries Data Management Team', 'datamanagement@duke.edu', 'urn:mace:incommon:duke.edu', true, 'Hello %{user_name},
Thank you for submitting your data management plan for feedback. Please send a follow-up email with the name of your plan to datamanagement@duke.edu to ensure we receive your request in a timely fashion.
', '["datamanagement@duke.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02der9h97', 'ROR', 'University of Connecticut', 'University of Connecticut (uconn.edu)', 'University of Connecticut | uconn.edu | UConn', 1, '100009073', 'http://uconn.edu/', '[]', '["UConn"]', '["Education"]',NULL,'Research Data Librarian', 'researchdata@uconn.edu', 'https://shibboleth.uconn.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdata@uconn.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/001tmjg57', 'ROR', 'University of Kansas', 'University of Kansas (ku.edu)', 'University of Kansas | ku.edu | KU ', 1, '100007859', 'http://www.ku.edu/', '["KU"]', '[]', '["Education"]',NULL,'KU Libraries', 'jamenebk@ku.edu', 'https://shibidp.ku.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jamenebk@ku.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00h6set76', 'ROR', 'Utah State University', 'Utah State University (usu.edu)', 'Utah State University | usu.edu | USU ', 1, '100006630', 'http://www.usu.edu/', '["USU"]', '[]', '["Education"]',NULL,'USU Data Librarian', 'researchdata@usu.edu', 'https://shibboleth.usu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdata@usu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05abbep66', 'ROR', 'Brandeis University', 'Brandeis University (brandeis.edu)', 'Brandeis University | brandeis.edu | ', 1, '100007864', 'http://www.brandeis.edu/', '[]', '[]', '["Education"]',NULL,'Email a Librarian', 'researchhelp@brandeis.edu', 'https://shibboleth.brandeis.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchhelp@brandeis.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01e3m7079', 'ROR', 'University of Cincinnati', 'University of Cincinnati (uc.edu)', 'University of Cincinnati | uc.edu | UC ', 1, '100008102', 'http://www.uc.edu/', '["UC"]', '[]', '["Education"]',NULL,'Research Data & GIS Services', 'AskData@uc.edu', 'https://login.uc.edu/idp/shibboleth', true, 'If you would like a member of the UC Libraries Research and Data Services team to review your data management plan, please contact us at ASKData@uc.edu. To ensure the best service for your grant proposal, please allow 5 days for review.
', '["AskData@uc.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/050qj5m48', 'ROR', 'University of Maine System', 'University of Maine System (maine.edu)', 'University of Maine System | maine.edu | UMS ', 1, '100010066', 'http://www.maine.edu/', '["UMS"]', '[]', '["Education"]',NULL,'Advanced Computing Group at the University of Maine', 'acg@maine.edu', 'https://idp.maine.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["acg@maine.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02jbv0t02', 'ROR', 'Lawrence Berkeley National Laboratory', 'Lawrence Berkeley National Laboratory (lbl.gov)', 'Lawrence Berkeley National Laboratory | lbl.gov | LBNL | LBL Berkeley Lab', 1, '100006235', 'http://www.lbl.gov/', '["LBNL","LBL"]', '["Berkeley Lab"]', '["Facility"]',NULL,'Contact LBL', 'ghamm@lbl.gov', 'urn:mace:incommon:lbl.gov', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ghamm@lbl.gov"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/019kgqr73', 'ROR', 'The University of Texas at Arlington', 'The University of Texas at Arlington (uta.edu)', 'The University of Texas at Arlington | uta.edu | UTA UT Arlington', 1, '100009497', 'http://www.uta.edu/uta/', '["UTA"]', '["UT Arlington"]', '["Education"]',NULL,'UTA Research Data Services', 'dataCAVE@uta.edu', 'https://idp.uta.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dataCAVE@uta.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/005781934', 'ROR', 'Baylor University', 'Baylor University (baylor.edu)', 'Baylor University | baylor.edu | ', 1, '100007492', 'http://www.baylor.edu/', '[]', '[]', '["Education"]',NULL,'Christina Chan-Park or Billie Peterson-Lugo', 'scholcomm@baylor.edu', 'https://shibboleth-2.baylor.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["scholcomm@baylor.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/048sx0r50', 'ROR', 'University of Houston', 'University of Houston (uh.edu)', 'University of Houston | uh.edu | UH ', 1, '100005914', 'http://www.uh.edu/', '["UH"]', '[]', '["Education"]',NULL,'Reid Boehm', 'riboehm@Central.UH.EDU', 'https://shibboleth.lib.uh.edu/idp/shibboleth', true, 'Thank you for your request. UH Research Data Management Librarian, Reid Boehm will respond within 2 business days. If you have additional questions about the request, please contact riboehm@uh.edu.
', '["riboehm@Central.UH.EDU"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01vx35703', 'ROR', 'East Carolina University', 'East Carolina University (ecu.edu)', 'East Carolina University | ecu.edu | ECU East Carolina', 1, '100008501', 'http://www.ecu.edu/', '["ECU"]', '["East Carolina"]', '["Education"]',NULL,'ECU Libraries', 'scholarlycomm@ecu.edu', 'https://sso.ecu.edu/idp/shibboleth', false, '
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["scholarlycomm@ecu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/012afjb06', 'ROR', 'Lehigh University', 'Lehigh University (www1.lehigh.edu)', 'Lehigh University | www1.lehigh.edu | ', 1, '100008234', 'http://www1.lehigh.edu/', '[]', '[]', '["Education"]',NULL,'LTS Data Curation Group', 'brs4@lehigh.edu', 'https://sso.cc.lehigh.edu/sso/saml2/idp/metadata.php', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["brs4@lehigh.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00y4zzh67', 'ROR', 'George Washington University', 'George Washington University (gwu.edu)', 'George Washington University | gwu.edu | GWU | GW ', 1, '100007108', 'http://www.gwu.edu/', '["GWU","GW"]', '[]', '["Education"]',NULL,'Megan Potterbusch - Data Services Librarian', 'mpotterbusch@gwu.edu', 'https://singlesignon.gwu.edu/idp/shibboleth', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at George Washington University. If you have questions about this action or about data management support at GW, please contact us at libdata@gwu.edu or email our Data Services Librarian directly at mpotterbusch@gwu.edu.
', '["mpotterbusch@gwu.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/049s0rh22', 'ROR', 'Dartmouth College', 'Dartmouth College (dartmouth.edu)', 'Dartmouth College | dartmouth.edu | ', 1, '100008299', 'http://dartmouth.edu/', '[]', '[]', '["Education"]',NULL,'Dartmouth OSP: Data managment plans', 'DMP-support@listserv.dartmouth.edu', 'urn:mace:incommon:dartmouth.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["DMP-support@listserv.dartmouth.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03vek6s52', 'ROR', 'Harvard University', 'Harvard University (harvard.edu)', 'Harvard University | harvard.edu | ', 1, '100007229', 'http://www.harvard.edu/', '[]', '[]', '["Education"]',NULL,'Harvard DMPTool Support', 'dmptool_support@harvard.edu', 'https://fed.huit.harvard.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool_support@harvard.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/013kjyp64', 'ROR', 'American Heart Association', 'American Heart Association (heart.org)', 'American Heart Association | heart.org | AHA Association for the Prevention and Relief of Heart Disease', 1, '100000968', 'http://www.heart.org/HEARTORG/', '["AHA"]', '["Association for the Prevention and Relief of Heart Disease"]', '["Nonprofit"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/006wxqw41', 'ROR', 'Gordon and Betty Moore Foundation', 'Gordon and Betty Moore Foundation (moore.org)', 'Gordon and Betty Moore Foundation | moore.org | ', 1, '100000936', 'https://www.moore.org/', '[]', '[]', '["Nonprofit"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01bj3aw27', 'ROR', 'United States Department of Energy', 'United States Department of Energy (energy.gov)', 'United States Department of Energy | energy.gov | ', 1, '100000015', 'http://www.energy.gov/', '[]', '[]', '["Government"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01cwqze88', 'ROR', 'National Institutes of Health', 'National Institutes of Health (nih.gov)', 'National Institutes of Health | nih.gov | NIH ', 1, '100000002', 'http://www.nih.gov/', '["NIH"]', '[]', '["Government"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/021nxhr62', 'ROR', 'National Science Foundation', 'National Science Foundation (nsf.gov)', 'National Science Foundation | nsf.gov | NSF ', 1, '100000001', 'http://www.nsf.gov/', '["NSF"]', '[]', '["Government"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0406gha72', 'ROR', 'University of Nevada, Las Vegas', 'University of Nevada, Las Vegas (unlv.edu)', 'University of Nevada, Las Vegas | unlv.edu | UNLV ', 1, '100004186', 'http://www.unlv.edu/', '["UNLV"]', '[]', '["Education"]',NULL,'UNLV Libraries', 'digitalscholarship@unlv.edu ', 'https://login.unlv.edu/FIM/sps/MyShib/saml20', false, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at your organisation. If you have questions pertaining to this action, please contact us at %{organisation_email}.
', '["digitalscholarship@unlv.edu "]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02sc3r913', 'ROR', 'Griffith University', 'Griffith University (griffith.edu.au)', 'Griffith University | griffith.edu.au | ', 1, '501100001791', 'http://www.griffith.edu.au/', '[]', '[]', '["Education"]',NULL,'Kelly Lennon', 'k.lennon@griffith.edu.au', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["k.lennon@griffith.edu.au"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04agmb972', 'ROR', 'Georgia Southern University', 'Georgia Southern University (georgiasouthern.edu)', 'Georgia Southern University | georgiasouthern.edu | ', 1, '100006376', 'http://www.georgiasouthern.edu/', '[]', '[]', '["Education"]',NULL,'Data Management Services', 'jmortimore@georgiasouthern.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jmortimore@georgiasouthern.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04dawnj30', 'ROR', 'University of North Carolina at Charlotte', 'University of North Carolina at Charlotte (uncc.edu)', 'University of North Carolina at Charlotte | uncc.edu | UNCC ', 1, '100010942', 'http://www.uncc.edu/', '["UNCC"]', '[]', '["Education"]',NULL,'Reese Manceaux', 'ramancea@uncc.edu', 'https://webauth.uncc.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ramancea@uncc.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/021v3qy27', 'ROR', 'University of Dayton', 'University of Dayton (udayton.edu)', 'University of Dayton | udayton.edu | ', 1, '100008413', 'https://www.udayton.edu/', '[]', '[]', '["Education"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', 'urn:mace:incommon:udayton.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/001575385', 'ROR', 'International Centre for Genetic Engineering and Biotechnology', 'International Centre for Genetic Engineering and Biotechnology (icgeb.org)', 'International Centre for Genetic Engineering and Biotechnology | icgeb.org | ICGEB', 0, NULL, 'https://www.icgeb.org/', '[]', '["ICGEB"]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02gr0tn14', 'ROR', 'Breast Cancer Resource Centre of Austin', 'Breast Cancer Resource Centre of Austin (bcrc.org)', 'Breast Cancer Resource Centre of Austin | bcrc.org | BCRC', 0, NULL, 'http://www.bcrc.org/', '[]', '["BCRC"]', '["Other"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03b5q4637', 'ROR', 'Educational Testing Service', 'Educational Testing Service (ets.org)', 'Educational Testing Service | ets.org | ETS ', 1, '100005704', 'https://www.ets.org/', '["ETS"]', '[]', '["Nonprofit"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01mqtzm43', 'ROR', 'Seville Institute of Microelectronics', 'Seville Institute of Microelectronics (imse-cnm.csic.es)', 'Seville Institute of Microelectronics | imse-cnm.csic.es | IMSE, CNM ', 0, NULL, 'http://www.imse-cnm.csic.es/', '["IMSE, CNM"]', '[]', '["Facility"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01nxc2t48', 'ROR', 'Montclair State University', 'Montclair State University (montclair.edu)', 'Montclair State University | montclair.edu | MSU Montclair State College', 1, '100010918', 'http://www.montclair.edu/', '["MSU"]', '["Montclair State College"]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/b4ab1dda', 'DMPTOOL', 'French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks', 'French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks (ifsttar.fr)', 'French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks | ifsttar.fr | ', 0, NULL, 'https://www.ifsttar.fr/accueil/', '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03bahkk91', 'ROR', 'Arkansas Tech University', 'Arkansas Tech University (atu.edu)', 'Arkansas Tech University | atu.edu | ATU ', 1, '100010072', 'http://www.atu.edu/', '["ATU"]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02sbj8547', 'ROR', 'Waynesburg University', 'Waynesburg University (waynesburg.edu)', 'Waynesburg University | waynesburg.edu | ', 0, NULL, 'http://www.waynesburg.edu/', '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/005gjjf63', 'ROR', 'National Psoriasis Foundation', 'National Psoriasis Foundation (psoriasis.org)', 'National Psoriasis Foundation | psoriasis.org | NPF ', 1, '100003185', 'https://www.psoriasis.org/', '["NPF"]', '[]', '["Nonprofit"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/002rgah83', 'ROR', 'Rheonix', 'Rheonix (United States) (rheonix.com)', 'Rheonix | rheonix.com | ', 0, NULL, 'https://rheonix.com/', '[]', '[]', '["Company"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01597g643', 'ROR', 'State University of New York at Oswego', 'State University of New York at Oswego (oswego.edu)', 'State University of New York at Oswego | oswego.edu | SUNY Oswego', 0, NULL, 'http://www.oswego.edu/', '[]', '["SUNY Oswego"]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01nftxb06', 'ROR', 'Leibniz Institute of Freshwater Ecology and Inland Fisheries', 'Leibniz Institute of Freshwater Ecology and Inland Fisheries (igb-berlin.de)', 'Leibniz Institute of Freshwater Ecology and Inland Fisheries | igb-berlin.de | IGB ', 0, NULL, 'http://www.igb-berlin.de/', '["IGB"]', '[]', '["Facility"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/97bea8fd', 'DMPTOOL', 'The Crofoot Research Center, Inc.', 'The Crofoot Research Center, Inc.', 'The Crofoot Research Center, Inc. | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/988054c8', 'DMPTOOL', 'Janssen Scientific Affairs, LLC', 'Janssen Scientific Affairs, LLC', 'Janssen Scientific Affairs, LLC | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); -INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/bd5f855a', 'DMPTOOL', 'Hager Sharp', 'Hager Sharp', 'Hager Sharp | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, CURDATE(), @default_super_id, CURDATE()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0153tk833', 'ROR', 'University of Virginia', 'University of Virginia (virginia.edu)', 'University of Virginia | virginia.edu | UVA ', 1, '100008457', 'http://www.virginia.edu/', '["UVA"]', '[]', '["Education"]', NULL, 'Data Management Consulting Group', 'dmconsult@virginia.edu', 'urn:mace:incommon:virginia.edu', true, 'The Research Data Management librarian from the University of Virginia Library will respond to your request within 48 hours. If you have questions pertaining to this action please consult us at dmconsult@virginia.edu.
', '["dmconsult@virginia.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0168r3w48', 'ROR', 'University of California, San Diego', 'University of California, San Diego (ucsd.edu)', 'University of California, San Diego | ucsd.edu | UCSD UC San Diego', 1, '100007911', 'http://ucsd.edu/', '["UCSD"]', '["UC San Diego"]', '["Education"]',NULL,'The Library - Research Data Curation Program', 'Research-Data-Curation@ucsd.edu', 'urn:mace:incommon:ucsd.edu', true, 'The Research Data Curation Program from the University of California, San Diego Library will respond to your request. If you have questions pertaining to this action please contact us at Research-Data-Curation@ucsd.edu
', '["Research-Data-Curation@ucsd.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01pp8nd67', 'ROR', 'Smithsonian Institution', 'Smithsonian Institution (si.edu)', 'Smithsonian Institution | si.edu | SI ', 1, '100000014', 'http://www.si.edu/', '["SI"]', '[]', '["Government"]', NULL, 'Research Data Management at SI', 'SI-RDM@si.edu', 'https://idp.si.edu/idp/shibboleth', true, 'Feedback/questions on using DMPTool can be directed to SI-RDM@si.edu
', '["SI-RDM@si.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/047426m28', 'ROR', 'University of Illinois Urbana-Champaign', 'University of Illinois Urbana-Champaign (illinois.edu)', 'University of Illinois Urbana-Champaign | illinois.edu | UIUC University of Illinois', 1, '100005302', 'http://illinois.edu/', '["UIUC"]', '["University of Illinois"]', '["Education"]',NULL,'UIUC Research Data Service', 'researchdata@library.illinois.edu', 'urn:mace:incommon:uiuc.edu', true, 'Hello %{user_name}.
If you would like staff from the Research Data Service at University of Illinois at Urbana-Champaign (UIUC) to review your DMP, please click the "Request Feedback" button below. We will respond to your request within 48 hours, if not sooner.
If you need a review urgently, please email us directly at researchdata@library.illinois.edu with the deadline for submission to UIUC\'s Sponsored Project Administration (SPA), a link to the funding announcement, and your draft DMP.
Sincerely,
RDS Staff
', '["researchdata@library.illinois.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01an7q238', 'ROR', 'University of California, Berkeley', 'University of California, Berkeley (berkeley.edu)', 'University of California, Berkeley | berkeley.edu | UCB UC Berkeley', 1, '100006978', 'http://www.berkeley.edu/', '["UCB"]', '["UC Berkeley"]', '["Education"]',NULL,'Anna Sackmann', 'asackmann@berkeley.edu', 'urn:mace:incommon:berkeley.edu', false, 'Dear %
"%
Please email %
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dataserv@ucdavis.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04gyf1771', 'ROR', 'University of California, Irvine', 'University of California, Irvine (uci.edu)', 'University of California, Irvine | uci.edu | UCI UC Irvine', 1, '100008476', 'http://uci.edu/', '["UCI"]', '["UC Irvine"]', '["Education"]',NULL,'Digital Scholarship Services', 'libdss@uci.edu', 'urn:mace:incommon:uci.edu', true, 'A data librarian from University of California, Irvine (UCI) will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at libdss@uci.edu.
', '["libdss@uci.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/046rm7j60', 'ROR', 'University of California, Los Angeles', 'University of California, Los Angeles (ucla.edu)', 'University of California, Los Angeles | ucla.edu | UCLA State Normal School at Los Angeles | University of California Southern Branch | University of California at Los Angeles', 1, '100007185', 'http://www.ucla.edu/', '["UCLA"]', '["State Normal School at Los Angeles","University of California Southern Branch","University of California at Los Angeles"]', '["Education"]',NULL,'UCLA Library Data Management Group', 'data@library.ucla.edu', 'urn:mace:incommon:ucla.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@library.ucla.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00d9ah105', 'ROR', 'University of California, Merced', 'University of California, Merced (ucmerced.edu)', 'University of California, Merced | ucmerced.edu | UCM UC Merced', 1, '100010945', 'http://www.ucmerced.edu/', '["UCM"]', '["UC Merced"]', '["Education"]',NULL,'UC Merced Data Curation', 'curation@ucmerced.edu', 'urn:mace:incommon:ucmerced.edu', true, 'Hello %{user_name},
Your plan "%{plan_name} has been submitted for feedback from the Digital Curation and Scholarship unit of the UC Merced Library. If you have questions about this or would like additional follow-up on this plan, please contact us at curation@ucmerced.edu.
', '["curation@ucmerced.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03nawhv43', 'ROR', 'University of California, Riverside', 'University of California, Riverside (ucr.edu)', 'University of California, Riverside | ucr.edu | UCR UC Riverside', 1, '100007602', 'http://www.ucr.edu/', '["UCR"]', '["UC Riverside"]', '["Education"]',NULL,'UCR Library Data Consultation', 'dataconsult-lib@ucr.edu', 'urn:mace:incommon:ucr.edu', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at your organisation. If you have questions pertaining to this action, please contact us at %{organisation_email}.
', '["dataconsult-lib@ucr.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/043mz5j54', 'ROR', 'University of California, San Francisco', 'University of California, San Francisco (ucsf.edu)', 'University of California, San Francisco | ucsf.edu | UCSF ', 1, '100008069', 'https://www.ucsf.edu/', '["UCSF"]', '[]', '["Education"]',NULL,'Ariel Deardorff', 'ariel.deardorff@ucsf.edu', 'urn:mace:incommon:ucsf.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ariel.deardorff@ucsf.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02t274463', 'ROR', 'University of California, Santa Barbara', 'University of California, Santa Barbara (ucsb.edu)', 'University of California, Santa Barbara | ucsb.edu | UCSB UC Santa Barbara', 1, '100007183', 'http://www.ucsb.edu/', '["UCSB"]', '["UC Santa Barbara"]', '["Education"]',NULL,'Email', 'rds@library.ucsb.edu', 'urn:mace:incommon:ucsb.edu', true, 'A data specialist from University of California, Santa Barbara (UCSB) will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at rds@library.ucsb.edu
', '["rds@library.ucsb.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03s65by71', 'ROR', 'University of California, Santa Cruz', 'University of California, Santa Cruz (ucsc.edu)', 'University of California, Santa Cruz | ucsc.edu | UCSC UC Santa Cruz', 1, '100006358', 'http://www.ucsc.edu/', '["UCSC"]', '["UC Santa Cruz"]', '["Education"]',NULL,'Contact a UCSC Librarian', 'research@library.ucsc.edu', 'urn:mace:incommon:ucsc.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["research@library.ucsc.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00pjdza24', 'ROR', 'University of California System', 'University of California System (universityofcalifornia.edu)', 'University of California System | universityofcalifornia.edu | UC ', 1, '100005595', 'http://www.universityofcalifornia.edu/', '["UC"]', '[]', '["Education"]',NULL,'UC3 Helpdesk', 'dmptool@ucop.edu', 'urn:mace:incommon:ucop.edu', true, 'Someone from the University of California Curation Center (UC3) will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at uc3@ucop.edu
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/024mw5h28', 'ROR', 'University of Chicago', 'University of Chicago (uchicago.edu)', 'University of Chicago | uchicago.edu | UC UChicago', 1, '100007234', 'http://www.uchicago.edu/', '["UC"]', '["UChicago"]', '["Education"]',NULL,'Library Data Services', 'data-help@uchicago.edu', 'urn:mace:incommon:uchicago.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data-help@uchicago.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/020yh1f96', 'ROR', 'Ohio State University Hospital', 'Ohio State University Hospital (wexnermedical.osu.edu)', 'Ohio State University Hospital | wexnermedical.osu.edu | ', 0, NULL, 'https://wexnermedical.osu.edu/locations-and-parking/university-hospital', '[]', '[]', '["Healthcare"]',NULL,'Data Management Services', 'datamanagement@osu.edu', 'urn:mace:incommon:osu.edu', true, 'Hello %{user_name},
Your plan has been submitted for feedback to the Data Management Services team at The Ohio State University Libraries. You should expect a response within 7 business days. If you have questions about your submission, please contact us at datamanagement@osu.edu.
', '["datamanagement@osu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00jmfr291', 'ROR', 'University of Michigan–Ann Arbor', 'University of Michigan–Ann Arbor (umich.edu)', 'University of Michigan–Ann Arbor | umich.edu | UM UMich', 1, '100007270', 'https://www.umich.edu/', '["UM"]', '["UMich"]', '["Education"]',NULL,'Research Data Services', 'researchdataservices@umich.edu', 'https://shibboleth.umich.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdataservices@umich.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/043mer456', 'ROR', 'University of Nebraska–Lincoln', 'University of Nebraska–Lincoln (unl.edu)', 'University of Nebraska–Lincoln | unl.edu | UNL | NU ', 1, '100008114', 'http://www.unl.edu/', '["UNL ","NU"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shib.unl.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03efmqc40', 'ROR', 'Arizona State University', 'Arizona State University (asu.edu)', 'Arizona State University | asu.edu | ASU ', 1, '100007482', 'http://www.asu.edu/', '["ASU"]', '[]', '["Education"]',NULL,'Contact ASU Library Researcher Support', 'researchsupport@asu.edu', 'urn:mace:incommon:asu.edu', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from a research librarian at the ASU Library. Please allow 48 hours Monday through Friday for someone to respond to your request.
If you have questions pertaining to this action, please contact us or visit the ASU Library Researcher Support for more information on project support.
Thank you,
ASU Library
Research and Publication Services
Arizona State University
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/000e0be47', 'ROR', 'Northwestern University', 'Northwestern University (northwestern.edu)', 'Northwestern University | northwestern.edu | NU ', 1, '100007059', 'http://www.northwestern.edu/', '["NU"]', '[]', '["Education"]',NULL,'eResearch at Northwestern University', 'e-research@northwestern.edu', 'urn:mace:incommon:northwestern.edu', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback. A data librarian from Northwestern University Libraries (NU) will respond to your request within 48 hours. If you have any questions please contact us at e-reserach@northwestern.edu.
', '["e-research@northwestern.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0130frc33', 'ROR', 'University of North Carolina at Chapel Hill', 'University of North Carolina at Chapel Hill (unc.edu)', 'University of North Carolina at Chapel Hill | unc.edu | UNC UNC-Chapel Hill', 1, '100007890', 'http://www.unc.edu/', '["UNC"]', '["UNC-Chapel Hill"]', '["Education"]',NULL,'The University of North Carolina at Chapel Hill', 'odumarchive@unc.edu', 'urn:mace:incommon:unc.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["odumarchive@unc.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05hs6h993', 'ROR', 'Michigan State University', 'Michigan State University (msu.edu)', 'Michigan State University | msu.edu | MSU ', 1, '100007709', 'https://msu.edu/', '["MSU"]', '[]', '["Education"]',NULL,'Ranti Junus', 'junus@msu.edu', 'urn:mace:incommon:msu.edu', true, 'A data librarian from MSU Libraries will respond to your request within 2 business days. If you have questions or would like to follow up, please contact Scout Calvert, calvert4@msu.edu.
', '["junus@msu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04p491231', 'ROR', 'Pennsylvania State University', 'Pennsylvania State University (psu.edu)', 'Pennsylvania State University | psu.edu | PSU Penn State', 1, '100008321', 'http://www.psu.edu/', '["PSU"]', '["Penn State"]', '["Education"]',NULL,'Briana Wham', 'bde125@psu.edu', 'urn:mace:incommon:psu.edu', true, 'Dear %{user_name},
"%{plan_name}" has been sent to your DMPtool account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["bde125@psu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02mpq6x41', 'ROR', 'University of Illinois at Chicago', 'University of Illinois at Chicago (uic.edu)', 'University of Illinois at Chicago | uic.edu | UIC ', 1, '100008522', 'http://www.uic.edu/uic/', '["UIC"]', '[]', '["Education"]',NULL,'UIC DMP help', 'lib-data@uic.edu', 'https://shibboleth.uic.edu/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["lib-data@uic.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/020qm1538', 'ROR', 'California State University System', 'California State University System (calstate.edu)', 'California State University System | calstate.edu | CSU Cal State', 0, NULL, 'http://www.calstate.edu/', '["CSU"]', '["Cal State"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp-co.calstate.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01c8f2y33', 'ROR', 'Moss Landing Marine Laboratories', 'Moss Landing Marine Laboratories (mlml.calstate.edu)', 'Moss Landing Marine Laboratories | mlml.calstate.edu | MLML ', 1, NULL, 'https://www.mlml.calstate.edu/', '["MLML"]', '[]', '["Facility"]',NULL,'Katie Lage, Librarian MLML/MBARI Research Library', 'klage@mlml.calstate.edu', 'urn:mace:incommon:mlml.calstate.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["klage@mlml.calstate.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0294hxs80', 'ROR', 'California State University Los Angeles', 'California State University Los Angeles (calstatela.edu)', 'California State University Los Angeles | calstatela.edu | CSULA Cal State LA', 0, NULL, 'http://www.calstatela.edu/', '["CSULA"]', '["Cal State LA"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idpp.calstatela.edu/idp', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03enmdz06', 'ROR', 'California State University, Fresno', 'California State University, Fresno (fresnostate.edu)', 'California State University, Fresno | fresnostate.edu | Fresno State University', 1, '100010075', 'http://www.fresnostate.edu/', '[]', '["Fresno State University"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shib-idp.its.csufresno.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00hj54h04', 'ROR', 'The University of Texas at Austin', 'The University of Texas at Austin (utexas.edu)', 'The University of Texas at Austin | utexas.edu | UT Austin', 1, '100008562', 'http://www.utexas.edu/', '[]', '["UT Austin"]', '["Education"]',NULL,'Meryl Brodsky', 'Meryl.Brodsky@austin.utexas.edu', 'https://enterprise.login.utexas.edu/idp/shibboleth', false, 'The Research Data Services unit at UT Libraries will respond to your request within 48 hours. If you have any questions about this or need more urgent attention, please contact j.trelogan@austin.utexas.edu.
', '["Meryl.Brodsky@austin.utexas.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04tj63d06', 'ROR', 'North Carolina State University', 'North Carolina State University (ncsu.edu)', 'North Carolina State University | ncsu.edu | NCSU ', 1, '100007703', 'https://www.ncsu.edu/', '["NCSU"]', '[]', '["Education"]',NULL,'NCSU Data Management Planning', 'library_datamanagement@ncsu.edu', 'urn:mace:incommon:ncsu.edu', true, '
Hi %{user_name},
Your plan "%{plan_name}" has been submitted for feedback from a librarian at NC State. We will review your draft DMP and get back to you within 5 business days. If you have any questions or need us to expedite our feedback to you, please contact us at library_datamanagement@ncsu.edu.
Thanks!
', '["library_datamanagement@ncsu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00za53h95', 'ROR', 'Johns Hopkins University', 'Johns Hopkins University (jhu.edu)', 'Johns Hopkins University | jhu.edu | JHU ', 1, '100007880', 'https://www.jhu.edu/', '["JHU"]', '[]', '["Education"]',NULL,'Contact for feedback on your plan and to archive your data in the JHU Data Archive', 'dataservices@jhu.edu', 'urn:mace:incommon:johnshopkins.edu', true, '
Your draft data management plan (DMP) has been sent to JHU Data Services. One of our consultants will provide feedback on your DMP within 2 business days.
Thank you,
JHU Data Services
(https://dataservices.library.jhu.edu/)
dataservices@jhu.edu
', '["dataservices@jhu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/008zs3103', 'ROR', 'Rice University', 'Rice University (rice.edu)', 'Rice University | rice.edu | William Marsh Rice University', 1, '100007863', 'http://www.rice.edu/', '[]', '["William Marsh Rice University"]', '["Education"]',NULL,'Lisa Spiro (Fondren Library)', ' reasearchdata@rice.edu', 'https://idp.rice.edu/idp/shibboleth', false, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at your organisation. If you have questions pertaining to this action, please contact us at %{organisation_email}.
', '[" reasearchdata@rice.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03m2x1q45', 'ROR', 'University of Arizona', 'University of Arizona (arizona.edu)', 'University of Arizona | arizona.edu | UA ', 1, '100007899', 'http://www.arizona.edu/', '["UA"]', '[]', '["Education"]',NULL,'Data Management Services Team', 'data-management@arizona.edu', 'urn:mace:incommon:arizona.edu', true, 'A specialist from University of Arizona will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at data-management@arizona.edu.
', '["data-management@arizona.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04zjtrb98', 'ROR', 'Old Dominion University', 'Old Dominion University (odu.edu)', 'Old Dominion University | odu.edu | ODU ', 1, '100009980', 'http://www.odu.edu/#prospective', '["ODU"]', '[]', '["Education"]',NULL,'Creating a Data Management Plan at ODU', 'swen@odu.edu', 'urn:mace:incommon:odu.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["swen@odu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02qt0xs84', 'ROR', 'Humboldt State University', 'Humboldt State University (humboldt.edu)', 'Humboldt State University | humboldt.edu | HSU ', 1, '100008121', 'http://www.humboldt.edu/', '["HSU"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:humboldt.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04t5xt781', 'ROR', 'Northeastern University', 'Northeastern University (northeastern.edu)', 'Northeastern University | northeastern.edu | NU | NEU ', 0, NULL, 'http://www.northeastern.edu/', '["NU","NEU"]', '[]', '["Education"]',NULL,'Contact Data Management at Northeastern', 'j.ferguson@northeastern.edu', 'https://neuidmsso.neu.edu/idp/shibboleth', true, 'Hello %{user_name},
Your data management plan "%{plan_name}" has been submitted for feedback from an administrator at your organization. Please allow 2 business days for us to respond with feedback.
If you have questions pertaining to this action, please contact us.
', '["j.ferguson@northeastern.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03v76x132', 'ROR', 'Yale University', 'Yale University (yale.edu)', 'Yale University | yale.edu | Collegiate School | Yale College', 1, '100005326', 'http://www.yale.edu', '[]', '["Collegiate School","Yale College"]', '["Education"]',NULL,'Yale DMPTool Administrator', 'barbara.esty@yale.edu', 'https://auth.yale.edu/idp/shibboleth', false, '
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["barbara.esty@yale.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02dgjyy92', 'ROR', 'University of Miami', 'University of Miami (miami.edu)', 'University of Miami | miami.edu | UM | U Miami ', 1, '100006686', 'http://www.miami.edu/', '["UM","U Miami"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://caneid.miami.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/027bzz146', 'ROR', 'California State University, Chico', 'California State University, Chico (csuchico.edu)', 'California State University, Chico | csuchico.edu | CSUC Chico State', 1, '100009972', 'http://www.csuchico.edu/', '["CSUC"]', '["Chico State"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shibboleth.csuchico.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02jqj7156', 'ROR', 'George Mason University', 'George Mason University (gmu.edu)', 'George Mason University | gmu.edu | ', 1, '100006369', 'https://www.gmu.edu/', '[]', '[]', '["Education"]',NULL,'Data Management Help', 'datahelp@gmu.edu', 'https://shibboleth.gmu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["datahelp@gmu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03hbp5t65', 'ROR', 'University of Idaho', 'University of Idaho (uidaho.edu)', 'University of Idaho | uidaho.edu | UI ', 0, NULL, 'http://www.uidaho.edu/', '["UI"]', '[]', '["Education"]',NULL,'U-Idaho Library', 'jkenyon@uidaho.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jkenyon@uidaho.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/028pmsz77', 'ROR', 'James Madison University', 'James Madison University (jmu.edu)', 'James Madison University | jmu.edu | JMU ', 1, '100008289', 'http://www.jmu.edu/', '["JMU"]', '[]', '["Education"]',NULL,'Head of Scholarly Communications Strategies', 'shorisyl@jmu.edu', 'urn:mace:incommon:jmu.edu', true, 'A librarian from James Madison University (JMU) will respond to your request within 48 hours. If you have questions pertaining to this action please contact shorisyl@jmu.edu.
', '["shorisyl@jmu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05by5hm18', 'ROR', 'California State Polytechnic University', 'California State Polytechnic University (cpp.edu)', 'California State Polytechnic University | cpp.edu | CPP Cal Poly Pomona | Cal Poly', 1, '100008508', 'http://www.cpp.edu/', '["CPP"]', '["Cal Poly Pomona","Cal Poly"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.calpoly.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00mkhxb43', 'ROR', 'University of Notre Dame', 'University of Notre Dame (nd.edu)', 'University of Notre Dame | nd.edu | ', 1, '100008109', 'https://www.nd.edu/', '[]', '[]', '["Education"]',NULL,'cds@nd.edu for DMP help.', 'cds@nd.edu', 'https://login.nd.edu/idp/shibboleth', true, 'Please contact Research Data Services <hl-research-data-services-list@nd.edu> for expert feedback, and check this online resource for ND DMP tips.
', '["cds@nd.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05p8z3f47', 'ROR', 'Purdue University System', 'Purdue University System (purdue.edu)', 'Purdue University System | purdue.edu | ', 0, NULL, 'http://www.purdue.edu/', '[]', '[]', '["Education"]',NULL,'Purdue Libraries Research Data - for help with data management plans', 'researchdata@purdue.edu', 'https://idp.purdue.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdata@purdue.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05fs6jp91', 'ROR', 'University of New Mexico', 'University of New Mexico (unm.edu)', 'University of New Mexico | unm.edu | UNM Universitatis Novus Mexico', 1, '100007179', 'http://www.unm.edu/', '["UNM"]', '["Universitatis Novus Mexico"]', '["Education"]',NULL,'Data curation at University of New Mexico', 'rds@unm.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["rds@unm.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01zkghx44', 'ROR', 'Georgia Institute of Technology', 'Georgia Institute of Technology (gatech.edu)', 'Georgia Institute of Technology | gatech.edu | GT Georgia Tech', 1, '100006778', 'http://www.gatech.edu/', '["GT"]', '["Georgia Tech"]', '["Education"]',NULL,'Georgia Institute of Technology', 'susan.parham@gatech.edu', 'https://idp.gatech.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["susan.parham@gatech.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01f5ytq51', 'ROR', 'Texas A&M University', 'Texas A&M University (tamu.edu)', 'Texas A&M University | tamu.edu | TAMU ', 1, '100007904', 'https://www.tamu.edu/', '["TAMU"]', '[]', '["Education"]',NULL,'TAMU DMPTool Administrator', 'xuzhihong@tamu.edu', 'urn:mace:incommon:tamu.edu', true, 'A data librarian from Texas A&M University will respond to your request within 48 hours. If you have questions pertaining to this action please contact us at xuzhihong@tamu.edu.
', '["xuzhihong@tamu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01y2jtd41', 'ROR', 'University of Wisconsin–Madison', 'University of Wisconsin–Madison (wisc.edu)', 'University of Wisconsin–Madison | wisc.edu | UW UW–Madison', 1, '100007015', 'http://www.wisc.edu/', '["UW"]', '["UW–Madison"]', '["Education"]',NULL,'Research Data Services', 'researchdata-working@lists.wisc.edu', 'https://login.wisc.edu/idp/shibboleth', true, 'An RDS Consultant from University of Wisconsin-Madison will be in touch about reviewing your DMP within two business days. If you have any questions pertaining to this action please contact us at researchdata-working@lists.wisc.edu. Thank you!
', '["researchdata-working@lists.wisc.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01kg8sb98', 'ROR', 'Indiana University', 'Indiana University (iu.edu)', 'Indiana University | iu.edu | IU ', 1, '100006733', 'http://www.iu.edu/', '["IU"]', '[]', '["Education"]',NULL,'Indiana University', 'iuswdata@indiana.edu', 'https://idp.login.iu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["iuswdata@indiana.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05h9q1g27', 'ROR', 'Texas State University', 'Texas State University (txstate.edu)', 'Texas State University | txstate.edu | ', 0, NULL, 'http://www.txstate.edu/', '[]', '[]', '["Education"]',NULL,'TXST Data Contact', 'digitalcollections@txstate.edu', 'https://authentic.txstate.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["digitalcollections@txstate.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/037s24f05', 'ROR', 'Clemson University', 'Clemson University (clemson.edu)', 'Clemson University | clemson.edu | Clemson Agricultural College of South Carolina', 1, '100006498', 'http://www.clemson.edu/', '[]', '["Clemson Agricultural College of South Carolina"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:clemson.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00ysfqy60', 'ROR', 'Oregon State University', 'Oregon State University (oregonstate.edu)', 'Oregon State University | oregonstate.edu | OSU ', 1, '100009612', 'http://oregonstate.edu/', '["OSU"]', '[]', '["Education"]',NULL,'OSU Research Data Services', 'ResearchDataServices@oregonstate.edu', 'https://login.oregonstate.edu/idp/shibboleth', true, 'Your plan will be reviewed by Research Data Services at Oregon State University. Please allow 48 hours for someone to respond to your request. If you have questions or comments about the process you can e-mail ResearchDataServices@oregonstate.edu. If you have an upcoming deadline (sooner than a week) please let us know by writing an e-mail to ResearchDataServices@oregonstate.edu.
', '["ResearchDataServices@oregonstate.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/052w4zt36', 'ROR', 'American University', 'American University (american.edu)', 'American University | american.edu | AU ', 1, '100010690', 'http://www.american.edu/', '["AU"]', '[]', '["Education"]',NULL,'Stefan Kramer', 'skramer@american.edu', 'https://idp.american.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["skramer@american.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04rswrd78', 'ROR', 'Iowa State University', 'Iowa State University (iastate.edu)', 'Iowa State University | iastate.edu | ISU Iowa State', 1, '100009227', 'http://www.iastate.edu/', '["ISU"]', '["Iowa State"]', '["Education"]',NULL,'Research Data Services - Univ. Library', 'datashare@iastate.edu', 'https://idp.iastate.edu/shibboleth', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback. We will be in touch with you within 48 hours or less but may need more time to review your plan.
If you have questions please contact us at datashare@iastate.edu
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@tulane.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03tzaeb71', 'ROR', 'University of Hawaii System', 'University of Hawaii System (hawaii.edu)', 'University of Hawaii System | hawaii.edu | UH University of Hawaii', 1, '100008782', 'http://www.hawaii.edu/', '["UH"]', '["University of Hawaii"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.hawaii.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02k3smh20', 'ROR', 'University of Kentucky', 'University of Kentucky (uky.edu)', 'University of Kentucky | uky.edu | ', 1, '100007472', 'http://www.uky.edu/', '[]', '[]', '["Education"]',NULL,'Adrian Ho', 'adrian.ho@uky.edu', 'https://ukidp.uky.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["adrian.ho@uky.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01j8e0j24', 'ROR', 'California State University, San Marcos', 'California State University, San Marcos (csusm.edu)', 'California State University, San Marcos | csusm.edu | CSUSM Cal State San Marcos', 1, '100007789', 'http://www.csusm.edu/', '["CSUSM"]', '["Cal State San Marcos"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.csusm.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00yn2fy02', 'ROR', 'Portland State University', 'Portland State University (pdx.edu)', 'Portland State University | pdx.edu | PSU ', 1, '100007083', 'https://www.pdx.edu/', '["PSU"]', '[]', '["Education"]',NULL,'Portland State University', 'lib-data-management@pdx.edu', 'https://sso.pdx.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["lib-data-management@pdx.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/017zqws13', 'ROR', 'University of Minnesota', 'University of Minnesota (twin-cities.umn.edu)', 'University of Minnesota | twin-cities.umn.edu | University of Minnesota, Twin Cities', 1, '100007913', 'http://twin-cities.umn.edu/', '[]', '["University of Minnesota, Twin Cities"]', '["Education"]',NULL,'University of Minnesota--Twin Cities', 'ljohnsto@umn.edu', 'urn:mace:incommon:umn.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ljohnsto@umn.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/031q21x57', 'ROR', 'University of Wisconsin–Milwaukee', 'University of Wisconsin–Milwaukee (www4.uwm.edu)', 'University of Wisconsin–Milwaukee | www4.uwm.edu | UWM UW–Milwaukee', 1, '100006817', 'http://www4.uwm.edu/', '["UWM"]', '["UW–Milwaukee"]', '["Education"]',NULL,'Kristin Briney, Data Services Librarian', 'briney@uwm.edu', 'https://idp.uwm.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["briney@uwm.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00v97ad02', 'ROR', 'University of North Texas', 'University of North Texas (unt.edu)', 'University of North Texas | unt.edu | UNT ', 1, '100008973', 'http://www.unt.edu/', '["UNT"]', '[]', '["Education"]',NULL,'Research Data Management Support', 'John.Martin@unt.edu', 'https://sso.unt.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["John.Martin@unt.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03r0ha626', 'ROR', 'University of Utah', 'University of Utah (utah.edu)', 'University of Utah | utah.edu | UU University of Deseret', 1, '100007747', 'http://www.utah.edu/', '["UU"]', '["University of Deseret"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:utah.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03czfpz43', 'ROR', 'Emory University', 'Emory University (emory.edu)', 'Emory University | emory.edu | ', 1, '100006939', 'http://www.emory.edu/home/index.html', '[]', '[]', '["Education"]',NULL,'Emory Data Management Plan Help', 'dataplans@emory.edu', 'https://login.emory.edu/idp/shibboleth', true, 'A data librarian from Emory University will respond to your request within 48 hours. If you have questions about reviews of data management plans, please contact us at dataplans@emory.edu.
', '["dataplans@emory.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03qt6ba18', 'ROR', 'Georgia State University', 'Georgia State University (gsu.edu)', 'Georgia State University | gsu.edu | GSU ', 1, '100008545', 'http://www.gsu.edu/', '["GSU"]', '[]', '["Education"]',NULL,'Data management at Georgia State University', 'libdatahelp@gsu.edu', 'https://idp.gsu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["libdatahelp@gsu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04bdffz58', 'ROR', 'Drexel University', 'Drexel University (drexel.edu)', 'Drexel University | drexel.edu | Drexel Institute | Drexel Institute of Technology', 1, '100008211', 'http://www.drexel.edu/', '[]', '["Drexel Institute","Drexel Institute of Technology"]', '["Education"]',NULL,'Data management at Drexel University', 'datamanagement@drexel.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["datamanagement@drexel.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02smfhw86', 'ROR', 'Virginia Tech', 'Virginia Tech (vt.edu)', 'Virginia Tech | vt.edu | Virginia Polytechnic Institute and State University', 1, '100007263', 'https://www.vt.edu/about/index.html', '[]', '["Virginia Polytechnic Institute and State University"]', '["Education"]',NULL,'Data Consultants for Questions and DMP Review Requests: dataservices@vt.edu', 'dataservices@vt.edu', 'urn:mace:incommon:vt.edu', true, 'A data management consultant from Virginia Tech University Libraries will respond to your feedback request with 2 business days. If you have other research data management questions or need more timely assistance please contact us at dataservices@vt.edu.
', '["dataservices@vt.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00f54p054', 'ROR', 'Stanford University', 'Stanford University (stanford.edu)', 'Stanford University | stanford.edu | SU Leland Stanford Junior University', 1, '100005492', 'http://www.stanford.edu/', '["SU"]', '["Leland Stanford Junior University"]', '["Education"]',NULL,'Stanford Libraries Data Management Services', 'ask-data-services@lists.stanford.edu', 'urn:mace:incommon:stanford.edu', true, 'Hello %{user_name},
Your Data Management Plan ("%{plan_name}")has been submitted to the data management experts at Stanford Libraries for review. Someone will review your plan and provide you with feedback shortly. If you have questions pertaining to this or an urgent deadline for the review, please contact us at ask-data-services@lists.stanford.edu.
Thank you.
', '["ask-data-services@lists.stanford.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/83c32cc7', 'DMPTOOL', 'University of Alabama', 'University of Alabama', 'University of Alabama | guides.lib.ua.edu | ', 0, NULL, 'http://guides.lib.ua.edu/rdmp', '[]', '[]', '["Education"]',NULL,'University of Alabama E-Science', 'rdmphelp@listserv.ua.edu', 'https://idp.ua.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["rdmphelp@listserv.ua.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00cvxb145', 'ROR', 'University of Washington', 'University of Washington (washington.edu)', 'University of Washington | washington.edu | UW ', 1, '100007812', 'http://www.washington.edu/', '["UW"]', '[]', '["Education"]',NULL,'UW Research Data Services Librarian', 'jmuil@uw.edu', 'urn:mace:incommon:washington.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jmuil@uw.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02y3ad647', 'ROR', 'University of Florida', 'University of Florida (ufl.edu)', 'University of Florida | ufl.edu | UF University of the State of Florida', 1, '100007698', 'http://www.ufl.edu/', '["UF"]', '["University of the State of Florida"]', '["Education"]',NULL,'Research Data Management at UF', 'Datamgmt-L@lists.ufl.edu', 'https://login.ufl.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["Datamgmt-L@lists.ufl.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/025r5qe02', 'ROR', 'Syracuse University', 'Syracuse University (syr.edu)', 'Syracuse University | syr.edu | SU ', 1, '100007126', 'http://www.syr.edu/', '["SU"]', '[]', '["Education"]',NULL,'Research Data Services at SU', 'DataSvcs@syr.edu', 'https://shibidp.syr.edu/idp/shibboleth', true, 'A data librarian from Syracuse University will respond to your request as soon as possible. If you have questions pertaining to this action please contact us at DataSvcs@syr.edu.
', '["DataSvcs@syr.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/034mtvk83', 'ROR', 'University of New Orleans', 'University of New Orleans (uno.edu)', 'University of New Orleans | uno.edu | UNO ', 1, '100009723', 'http://www.uno.edu/', '["UNO"]', '[]', '["Education"]',NULL,'UNO Data management', 'dmp@uno.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmp@uno.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05bnh6r87', 'ROR', 'Cornell University', 'Cornell University (cornell.edu)', 'Cornell University | cornell.edu | CU ', 1, '100007231', 'http://www.cornell.edu/', '["CU"]', '[]', '["Education"]',NULL,'Cornell\'s Research Data Management Service Group (RDMSG)', 'rdmsg-help@cornell.edu', 'https://shibidp.cit.cornell.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["rdmsg-help@cornell.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0190ak572', 'ROR', 'New York University', 'New York University (nyu.edu)', 'New York University | nyu.edu | NYU ', 1, '100006732', 'http://www.nyu.edu/', '["NYU"]', '[]', '["Education"]',NULL,'DMP Help', 'data.services@nyu.edu', 'urn:mace:incommon:nyu.edu', true, 'Hello %{user_name}! Your plan, "%{plan_name}", has been sent to a data librarian at NYU Data Services who will respond to your request within 48 hours. If you have questions pertaining to this request please contact us at %{organisation_email}.
', '["data.services@nyu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/022kthw22', 'ROR', 'University of Rochester', 'University of Rochester (rochester.edu)', 'University of Rochester | rochester.edu | UR ', 1, '100008091', 'https://www.rochester.edu/', '["UR"]', '[]', '["Education"]',NULL,'University of Rochester Data Management', 's.pugachev@rochester.edu', 'https://shib2.its.rochester.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["s.pugachev@rochester.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05dk0ce17', 'ROR', 'Washington State University', 'Washington State University (wsu.edu)', 'Washington State University | wsu.edu | WSU ', 1, '100007588', 'https://wsu.edu/', '["WSU"]', '[]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://shibidp.wsu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02nkdxk79', 'ROR', 'Virginia Commonwealth University', 'Virginia Commonwealth University (vcu.edu)', 'Virginia Commonwealth University | vcu.edu | VCU ', 1, '100009238', 'http://www.vcu.edu/', '["VCU"]', '[]', '["Education"]',NULL,'VCU Libraries RDM Team', 'libdatahelp@vcu.edu', 'https://shibboleth.vcu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["libdatahelp@vcu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01yc7t268', 'ROR', 'Washington University in St. Louis', 'Washington University in St. Louis (wustl.edu)', 'Washington University in St. Louis | wustl.edu | WUSTL ', 1, '100007268', 'http://wustl.edu/', '["WUSTL"]', '[]', '["Education"]',NULL,'Jennifer Moore', 'j.moore@wustl.edu', 'https://login.wustl.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["j.moore@wustl.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00hx57361', 'ROR', 'Princeton University', 'Princeton University (princeton.edu)', 'Princeton University | princeton.edu | College of New Jersey', 1, '100006734', 'http://www.princeton.edu/main/', '[]', '["College of New Jersey"]', '["Education"]',NULL,'Princeton Research Data Service', 'prds@princeton.edu', 'https://idp.princeton.edu/idp/shibboleth', true, 'Hello %{user_name},
Thank you for submitting your plan for feedback. Please allow 24-48 hours for someone to respond to your request. Meanwhile, if you have any additional questions, please contact us at prds@princeton.edu, or feel free to schedule a consultation from our website: https://researchdata.princeton.edu. Thanks!
Best,
Princeton Research Data Service Team
', '["prds@princeton.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00ds41r10', 'ROR', 'Carnegie Mellon University Australia', 'Carnegie Mellon University Australia (australia.cmu.edu)', 'Carnegie Mellon University Australia | australia.cmu.edu | CMU ', 0, NULL, 'https://www.australia.cmu.edu/', '["CMU"]', '[]', '["Education"]',NULL,'Contact University Libraries Data Services for help with data management plans', 'data@cmu.libanswers.com', 'https://login.cmu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@cmu.libanswers.com"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02ttsq026', 'ROR', 'University of Colorado Boulder', 'University of Colorado Boulder (colorado.edu)', 'University of Colorado Boulder | colorado.edu | UCB CU-Boulder', 1, '100007493', 'http://www.colorado.edu/', '["UCB"]', '["CU-Boulder"]', '["Education"]',NULL,'Get Help at CU Boulder', 'crdds@colorado.edu', 'https://fedauth.colorado.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["crdds@colorado.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/ed51675d', 'DMPTOOL', 'Weill Cornell Medicine', 'Weill Cornell Medicine', 'Weill Cornell Medicine | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'WCM DMPTool Admin', 'drw2004@med.cornell.edu', 'https://login.weill.cornell.edu/idp', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["drw2004@med.cornell.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05qwgg493', 'ROR', 'Boston University', 'Boston University (bu.edu)', 'Boston University | bu.edu | BU Boston U', 1, '100007161', 'http://www.bu.edu/', '["BU"]', '["Boston U"]', '["Education"]',NULL,'BU Research Data Management', 'data@bu.edu', 'https://shib.bu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["data@bu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00kx1jb78', 'ROR', 'Temple University', 'Temple University (temple.edu)', 'Temple University | temple.edu | ', 1, '100005806', 'http://www.temple.edu/', '[]', '[]', '["Education"]',NULL,'Temple RDS', 'tul-rds@temple.edu', 'https://fim.temple.edu/idp/shibboleth', true, 'Dear %{user_name}, We received your request for feedback on your plan, %{plan_name} .
A librarian from Temple University will respond to your request within 3 business days. If you have questions pertaining to this action, please contact us at tul-rds@temple.edu.
Thank you.
', '["tul-rds@temple.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02e3zdp86', 'ROR', 'Boise State University', 'Boise State University (boisestate.edu)', 'Boise State University | boisestate.edu | BSU ', 1, '100007233', 'https://www.boisestate.edu/', '["BSU"]', '[]', '["Education"]',NULL,'Boise State Data Management Support', 'datamanagement@boisestate.edu', 'https://idp.boisestate.edu/idp/shibboleth', false, 'A data librarian from Boise State University will respond to your request within 2 business days. If you have questions pertaining to this action, pease contact us at datamanagement@boisestate.edu.
', '["datamanagement@boisestate.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05qghxh33', 'ROR', 'Stony Brook University', 'Stony Brook University (stonybrook.edu)', 'Stony Brook University | stonybrook.edu | SBU SUNY Stony Brook', 1, '100007259', 'http://www.stonybrook.edu/', '["SBU"]', '["SUNY Stony Brook"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'urn:mace:incommon:stonybrook.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/020f3ap87', 'ROR', 'University of Tennessee at Knoxville', 'University of Tennessee at Knoxville (utk.edu)', 'University of Tennessee at Knoxville | utk.edu | UTK | UT University of Tennessee', 1, '100008526', 'http://www.utk.edu/', '["UTK","UT"]', '["University of Tennessee"]', '["Education"]',NULL,'Contact the Data Services Team', 'dataservices@utk.edu', 'https://idp.utk.edu/idp/shibboleth', true, 'Thank you for submitting your data management plan through the DMPTool.
Your request for feedback has been submitted to the Data Services Team at the UT Libraries. Any feedback will be provided within 3 business days through the DMPTool.
If you have any questions in the meantime, please contact the Data Services Team at dataservices@utk.edu.
', '["dataservices@utk.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01g9vbr38', 'ROR', 'Oklahoma State University', 'Oklahoma State University (go.okstate.edu)', 'Oklahoma State University | go.okstate.edu | OSU Oklahoma State', 1, '100007808', 'http://go.okstate.edu/', '["OSU"]', '["Oklahoma State"]', '["Education"]',NULL,'CDL/UC3', 'dmptool@ucop.edu', 'https://idp.okstate.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00py81415', 'ROR', 'Duke University', 'Duke University (duke.edu)', 'Duke University | duke.edu | ', 1, '100006510', 'http://www.duke.edu/', '[]', '[]', '["Education"]',NULL,'Duke University Libraries Data Management Team', 'datamanagement@duke.edu', 'urn:mace:incommon:duke.edu', true, 'Hello %{user_name},
Thank you for submitting your data management plan for feedback. Please send a follow-up email with the name of your plan to datamanagement@duke.edu to ensure we receive your request in a timely fashion.
', '["datamanagement@duke.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02der9h97', 'ROR', 'University of Connecticut', 'University of Connecticut (uconn.edu)', 'University of Connecticut | uconn.edu | UConn', 1, '100009073', 'http://uconn.edu/', '[]', '["UConn"]', '["Education"]',NULL,'Research Data Librarian', 'researchdata@uconn.edu', 'https://shibboleth.uconn.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdata@uconn.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/001tmjg57', 'ROR', 'University of Kansas', 'University of Kansas (ku.edu)', 'University of Kansas | ku.edu | KU ', 1, '100007859', 'http://www.ku.edu/', '["KU"]', '[]', '["Education"]',NULL,'KU Libraries', 'jamenebk@ku.edu', 'https://shibidp.ku.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jamenebk@ku.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00h6set76', 'ROR', 'Utah State University', 'Utah State University (usu.edu)', 'Utah State University | usu.edu | USU ', 1, '100006630', 'http://www.usu.edu/', '["USU"]', '[]', '["Education"]',NULL,'USU Data Librarian', 'researchdata@usu.edu', 'https://shibboleth.usu.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchdata@usu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/05abbep66', 'ROR', 'Brandeis University', 'Brandeis University (brandeis.edu)', 'Brandeis University | brandeis.edu | ', 1, '100007864', 'http://www.brandeis.edu/', '[]', '[]', '["Education"]',NULL,'Email a Librarian', 'researchhelp@brandeis.edu', 'https://shibboleth.brandeis.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["researchhelp@brandeis.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01e3m7079', 'ROR', 'University of Cincinnati', 'University of Cincinnati (uc.edu)', 'University of Cincinnati | uc.edu | UC ', 1, '100008102', 'http://www.uc.edu/', '["UC"]', '[]', '["Education"]',NULL,'Research Data & GIS Services', 'AskData@uc.edu', 'https://login.uc.edu/idp/shibboleth', true, 'If you would like a member of the UC Libraries Research and Data Services team to review your data management plan, please contact us at ASKData@uc.edu. To ensure the best service for your grant proposal, please allow 5 days for review.
', '["AskData@uc.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/050qj5m48', 'ROR', 'University of Maine System', 'University of Maine System (maine.edu)', 'University of Maine System | maine.edu | UMS ', 1, '100010066', 'http://www.maine.edu/', '["UMS"]', '[]', '["Education"]',NULL,'Advanced Computing Group at the University of Maine', 'acg@maine.edu', 'https://idp.maine.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["acg@maine.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02jbv0t02', 'ROR', 'Lawrence Berkeley National Laboratory', 'Lawrence Berkeley National Laboratory (lbl.gov)', 'Lawrence Berkeley National Laboratory | lbl.gov | LBNL | LBL Berkeley Lab', 1, '100006235', 'http://www.lbl.gov/', '["LBNL","LBL"]', '["Berkeley Lab"]', '["Facility"]',NULL,'Contact LBL', 'ghamm@lbl.gov', 'urn:mace:incommon:lbl.gov', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ghamm@lbl.gov"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/019kgqr73', 'ROR', 'The University of Texas at Arlington', 'The University of Texas at Arlington (uta.edu)', 'The University of Texas at Arlington | uta.edu | UTA UT Arlington', 1, '100009497', 'http://www.uta.edu/uta/', '["UTA"]', '["UT Arlington"]', '["Education"]',NULL,'UTA Research Data Services', 'dataCAVE@uta.edu', 'https://idp.uta.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dataCAVE@uta.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/005781934', 'ROR', 'Baylor University', 'Baylor University (baylor.edu)', 'Baylor University | baylor.edu | ', 1, '100007492', 'http://www.baylor.edu/', '[]', '[]', '["Education"]',NULL,'Christina Chan-Park or Billie Peterson-Lugo', 'scholcomm@baylor.edu', 'https://shibboleth-2.baylor.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["scholcomm@baylor.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/048sx0r50', 'ROR', 'University of Houston', 'University of Houston (uh.edu)', 'University of Houston | uh.edu | UH ', 1, '100005914', 'http://www.uh.edu/', '["UH"]', '[]', '["Education"]',NULL,'Reid Boehm', 'riboehm@Central.UH.EDU', 'https://shibboleth.lib.uh.edu/idp/shibboleth', true, 'Thank you for your request. UH Research Data Management Librarian, Reid Boehm will respond within 2 business days. If you have additional questions about the request, please contact riboehm@uh.edu.
', '["riboehm@Central.UH.EDU"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01vx35703', 'ROR', 'East Carolina University', 'East Carolina University (ecu.edu)', 'East Carolina University | ecu.edu | ECU East Carolina', 1, '100008501', 'http://www.ecu.edu/', '["ECU"]', '["East Carolina"]', '["Education"]',NULL,'ECU Libraries', 'scholarlycomm@ecu.edu', 'https://sso.ecu.edu/idp/shibboleth', false, '
Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["scholarlycomm@ecu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/012afjb06', 'ROR', 'Lehigh University', 'Lehigh University (www1.lehigh.edu)', 'Lehigh University | www1.lehigh.edu | ', 1, '100008234', 'http://www1.lehigh.edu/', '[]', '[]', '["Education"]',NULL,'LTS Data Curation Group', 'brs4@lehigh.edu', 'https://sso.cc.lehigh.edu/sso/saml2/idp/metadata.php', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["brs4@lehigh.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/00y4zzh67', 'ROR', 'George Washington University', 'George Washington University (gwu.edu)', 'George Washington University | gwu.edu | GWU | GW ', 1, '100007108', 'http://www.gwu.edu/', '["GWU","GW"]', '[]', '["Education"]',NULL,'Megan Potterbusch - Data Services Librarian', 'mpotterbusch@gwu.edu', 'https://singlesignon.gwu.edu/idp/shibboleth', true, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at George Washington University. If you have questions about this action or about data management support at GW, please contact us at libdata@gwu.edu or email our Data Services Librarian directly at mpotterbusch@gwu.edu.
', '["mpotterbusch@gwu.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/049s0rh22', 'ROR', 'Dartmouth College', 'Dartmouth College (dartmouth.edu)', 'Dartmouth College | dartmouth.edu | ', 1, '100008299', 'http://dartmouth.edu/', '[]', '[]', '["Education"]',NULL,'Dartmouth OSP: Data managment plans', 'DMP-support@listserv.dartmouth.edu', 'urn:mace:incommon:dartmouth.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["DMP-support@listserv.dartmouth.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03vek6s52', 'ROR', 'Harvard University', 'Harvard University (harvard.edu)', 'Harvard University | harvard.edu | ', 1, '100007229', 'http://www.harvard.edu/', '[]', '[]', '["Education"]',NULL,'Harvard DMPTool Support', 'dmptool_support@harvard.edu', 'https://fed.huit.harvard.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool_support@harvard.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/013kjyp64', 'ROR', 'American Heart Association', 'American Heart Association (heart.org)', 'American Heart Association | heart.org | AHA Association for the Prevention and Relief of Heart Disease', 1, '100000968', 'http://www.heart.org/HEARTORG/', '["AHA"]', '["Association for the Prevention and Relief of Heart Disease"]', '["Nonprofit"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/006wxqw41', 'ROR', 'Gordon and Betty Moore Foundation', 'Gordon and Betty Moore Foundation (moore.org)', 'Gordon and Betty Moore Foundation | moore.org | ', 1, '100000936', 'https://www.moore.org/', '[]', '[]', '["Nonprofit"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01bj3aw27', 'ROR', 'United States Department of Energy', 'United States Department of Energy (energy.gov)', 'United States Department of Energy | energy.gov | ', 1, '100000015', 'http://www.energy.gov/', '[]', '[]', '["Government"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01cwqze88', 'ROR', 'National Institutes of Health', 'National Institutes of Health (nih.gov)', 'National Institutes of Health | nih.gov | NIH ', 1, '100000002', 'http://www.nih.gov/', '["NIH"]', '[]', '["Government"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/021nxhr62', 'ROR', 'National Science Foundation', 'National Science Foundation (nsf.gov)', 'National Science Foundation | nsf.gov | NSF ', 1, '100000001', 'http://www.nsf.gov/', '["NSF"]', '[]', '["Government"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/0406gha72', 'ROR', 'University of Nevada, Las Vegas', 'University of Nevada, Las Vegas (unlv.edu)', 'University of Nevada, Las Vegas | unlv.edu | UNLV ', 1, '100004186', 'http://www.unlv.edu/', '["UNLV"]', '[]', '["Education"]',NULL,'UNLV Libraries', 'digitalscholarship@unlv.edu ', 'https://login.unlv.edu/FIM/sps/MyShib/saml20', false, 'Hello %{user_name}.
Your plan "%{plan_name}" has been submitted for feedback from an administrator at your organisation. If you have questions pertaining to this action, please contact us at %{organisation_email}.
', '["digitalscholarship@unlv.edu "]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02sc3r913', 'ROR', 'Griffith University', 'Griffith University (griffith.edu.au)', 'Griffith University | griffith.edu.au | ', 1, '501100001791', 'http://www.griffith.edu.au/', '[]', '[]', '["Education"]',NULL,'Kelly Lennon', 'k.lennon@griffith.edu.au', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["k.lennon@griffith.edu.au"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04agmb972', 'ROR', 'Georgia Southern University', 'Georgia Southern University (georgiasouthern.edu)', 'Georgia Southern University | georgiasouthern.edu | ', 1, '100006376', 'http://www.georgiasouthern.edu/', '[]', '[]', '["Education"]',NULL,'Data Management Services', 'jmortimore@georgiasouthern.edu', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["jmortimore@georgiasouthern.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/04dawnj30', 'ROR', 'University of North Carolina at Charlotte', 'University of North Carolina at Charlotte (uncc.edu)', 'University of North Carolina at Charlotte | uncc.edu | UNCC ', 1, '100010942', 'http://www.uncc.edu/', '["UNCC"]', '[]', '["Education"]',NULL,'Reese Manceaux', 'ramancea@uncc.edu', 'https://webauth.uncc.edu/idp/shibboleth', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["ramancea@uncc.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/021v3qy27', 'ROR', 'University of Dayton', 'University of Dayton (udayton.edu)', 'University of Dayton | udayton.edu | ', 1, '100008413', 'https://www.udayton.edu/', '[]', '[]', '["Education"]',NULL,'California Digital Library helpdesk', 'dmptool@ucop.edu', 'urn:mace:incommon:udayton.edu', false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '["dmptool@ucop.edu"]', true, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/001575385', 'ROR', 'International Centre for Genetic Engineering and Biotechnology', 'International Centre for Genetic Engineering and Biotechnology (icgeb.org)', 'International Centre for Genetic Engineering and Biotechnology | icgeb.org | ICGEB', 0, NULL, 'https://www.icgeb.org/', '[]', '["ICGEB"]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02gr0tn14', 'ROR', 'Breast Cancer Resource Centre of Austin', 'Breast Cancer Resource Centre of Austin (bcrc.org)', 'Breast Cancer Resource Centre of Austin | bcrc.org | BCRC', 0, NULL, 'http://www.bcrc.org/', '[]', '["BCRC"]', '["Other"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03b5q4637', 'ROR', 'Educational Testing Service', 'Educational Testing Service (ets.org)', 'Educational Testing Service | ets.org | ETS ', 1, '100005704', 'https://www.ets.org/', '["ETS"]', '[]', '["Nonprofit"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01mqtzm43', 'ROR', 'Seville Institute of Microelectronics', 'Seville Institute of Microelectronics (imse-cnm.csic.es)', 'Seville Institute of Microelectronics | imse-cnm.csic.es | IMSE, CNM ', 0, NULL, 'http://www.imse-cnm.csic.es/', '["IMSE, CNM"]', '[]', '["Facility"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01nxc2t48', 'ROR', 'Montclair State University', 'Montclair State University (montclair.edu)', 'Montclair State University | montclair.edu | MSU Montclair State College', 1, '100010918', 'http://www.montclair.edu/', '["MSU"]', '["Montclair State College"]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/b4ab1dda', 'DMPTOOL', 'French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks', 'French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks (ifsttar.fr)', 'French Institute of Science and Technology for Transport, Spatial Planning, Development and Networks | ifsttar.fr | ', 0, NULL, 'https://www.ifsttar.fr/accueil/', '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/03bahkk91', 'ROR', 'Arkansas Tech University', 'Arkansas Tech University (atu.edu)', 'Arkansas Tech University | atu.edu | ATU ', 1, '100010072', 'http://www.atu.edu/', '["ATU"]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/02sbj8547', 'ROR', 'Waynesburg University', 'Waynesburg University (waynesburg.edu)', 'Waynesburg University | waynesburg.edu | ', 0, NULL, 'http://www.waynesburg.edu/', '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/005gjjf63', 'ROR', 'National Psoriasis Foundation', 'National Psoriasis Foundation (psoriasis.org)', 'National Psoriasis Foundation | psoriasis.org | NPF ', 1, '100003185', 'https://www.psoriasis.org/', '["NPF"]', '[]', '["Nonprofit"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/002rgah83', 'ROR', 'Rheonix', 'Rheonix (United States) (rheonix.com)', 'Rheonix | rheonix.com | ', 0, NULL, 'https://rheonix.com/', '[]', '[]', '["Company"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01597g643', 'ROR', 'State University of New York at Oswego', 'State University of New York at Oswego (oswego.edu)', 'State University of New York at Oswego | oswego.edu | SUNY Oswego', 0, NULL, 'http://www.oswego.edu/', '[]', '["SUNY Oswego"]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://ror.org/01nftxb06', 'ROR', 'Leibniz Institute of Freshwater Ecology and Inland Fisheries', 'Leibniz Institute of Freshwater Ecology and Inland Fisheries (igb-berlin.de)', 'Leibniz Institute of Freshwater Ecology and Inland Fisheries | igb-berlin.de | IGB ', 0, NULL, 'http://www.igb-berlin.de/', '["IGB"]', '[]', '["Facility"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/97bea8fd', 'DMPTOOL', 'The Crofoot Research Center, Inc.', 'The Crofoot Research Center, Inc.', 'The Crofoot Research Center, Inc. | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/988054c8', 'DMPTOOL', 'Janssen Scientific Affairs, LLC', 'Janssen Scientific Affairs, LLC', 'Janssen Scientific Affairs, LLC | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); +INSERT INTO `affiliations` (`uri`, `provenance`, `name`, `displayName`, `searchName`, `funder`, `fundrefId`, `homepage`, `acronyms`, `aliases`, `types`, `logoName`, `contactName`, `contactEmail`, `ssoEntityId`, `feedbackEnabled`, `feedbackMessage`, `feedbackEmails`, `managed`, `createdById`, `created`, `modifiedById`, `modified`) VALUES ('https://dmptool.org/affiliations/bd5f855a', 'DMPTOOL', 'Hager Sharp', 'Hager Sharp', 'Hager Sharp | | ', 0, NULL, NULL, '[]', '[]', '["Education"]',NULL,'', '', NULL, false, 'Dear %{user_name},
"%{plan_name}" has been sent to your %{application_name} account administrator for feedback.
Please email %{organisation_email} with any questions about this process.
', '[]', false, @default_super_id, NOW(), @default_super_id, NOW()); -- Assign the email domain for each affiliation based on the homepage INSERT INTO `affiliationEmailDomains` (`affiliationId`, `emailDomain`, `createdById`, `created`, `modifiedById`, `modified`) @@ -162,7 +162,7 @@ INSERT INTO `affiliationEmailDomains` (`affiliationId`, `emailDomain`, `createdB '^www\\.', '' )) AS emailDomain, - @default_super_id, CURDATE(), @default_super_id, CURDATE() + @default_super_id, NOW(), @default_super_id, NOW() FROM `affiliations` WHERE homepage LIKE 'http%' ); diff --git a/data-migrations/local-only/2025-11-20-0836-seed-templates.sql b/data-migrations/local-only/2025-11-20-0836-seed-templates.sql index ef2d5bcb..47987f52 100644 --- a/data-migrations/local-only/2025-11-20-0836-seed-templates.sql +++ b/data-migrations/local-only/2025-11-20-0836-seed-templates.sql @@ -13,4462 +13,4462 @@ SET @default_funder2_id := (SELECT userId FROM userEmails WHERE email = CONCAT(' -- ======================================================== -- Default affiliation templates -- ======================================================== -INSERT INTO templates (id, latestPublishVisibility, latestPublishVersion, latestPublishDate, ownerId, name, description, bestPractice, languageId, createdById, created, modifiedById, modified) VALUES (59, 'PUBLIC', NULL, NULL, 'https://ror.org/03yrm5c26', 'Copy of NIH-GDS: Genomic Data Sharing', 'Copy of NIH-GDS: Genomic Data Sharing', 0, 'en-US', @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO templates (id, latestPublishVisibility, latestPublishVersion, latestPublishDate, ownerId, name, description, bestPractice, languageId, createdById, created, modifiedById, modified) VALUES (73, 'PUBLIC', NULL, NULL, 'https://ror.org/03yrm5c26', 'NSF Generic - informal review', 'NSF Generic - informal review
http://www.dcc.ac.uk/resources/how-guides/develop-data-plan
', 1, 'en-US', @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); +INSERT INTO templates (id, latestPublishVisibility, latestPublishVersion, latestPublishDate, ownerId, name, description, bestPractice, languageId, createdById, created, modifiedById, modified) VALUES (59, 'PUBLIC', NULL, NULL, 'https://ror.org/03yrm5c26', 'Copy of NIH-GDS: Genomic Data Sharing', 'Copy of NIH-GDS: Genomic Data Sharing', 0, 'en-US', @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO templates (id, latestPublishVisibility, latestPublishVersion, latestPublishDate, ownerId, name, description, bestPractice, languageId, createdById, created, modifiedById, modified) VALUES (73, 'PUBLIC', NULL, NULL, 'https://ror.org/03yrm5c26', 'NSF Generic - informal review', 'NSF Generic - informal review
http://www.dcc.ac.uk/resources/how-guides/develop-data-plan
', 1, 'en-US', @default_admin_id, NOW(), @default_admin_id, NOW()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (256, 59, 'Request for an exception to submission', '', '', '', 0, 6, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (255, 59, 'Appropriate uses of the data', '', '', '', 0, 5, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (254, 59, 'IRB assurance of genomic data sharing plan', '', '', '', 0, 4, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (251, 59, 'Data type', '', '', '', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (252, 59, 'Data repository', '', '', '', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (253, 59, 'Data submission and release timeline', '', '', '', 0, 3, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (302, 73, 'Plans for archiving and preservation', '', '', '', 0, 4, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (301, 73, 'Policies for re-use, redistribution', '', '', '', 0, 3, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (300, 73, 'Data and metadata standards', '', '', '', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (299, 73, 'Types of data produced', '', '', '', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (437, 100, 'Responsibilities and Resources', '', '', '', 0, 7, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (436, 100, 'Data Sharing', '', '', '', 0, 6, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (435, 100, 'Selection and Preservation', '', '', '', 0, 5, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (434, 100, 'Storage and Backup', '', '', '', 0, 4, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (433, 100, 'Ethics and Legal Compliance', '', '', '', 0, 3, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (432, 100, 'Documentation and Metadata', '', '', '', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (431, 100, 'Data Collection', '', '', '', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (256, 59, 'Request for an exception to submission', '', '', '', 0, 6, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (255, 59, 'Appropriate uses of the data', '', '', '', 0, 5, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (254, 59, 'IRB assurance of genomic data sharing plan', '', '', '', 0, 4, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (251, 59, 'Data type', '', '', '', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (252, 59, 'Data repository', '', '', '', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (253, 59, 'Data submission and release timeline', '', '', '', 0, 3, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (302, 73, 'Plans for archiving and preservation', '', '', '', 0, 4, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (301, 73, 'Policies for re-use, redistribution', '', '', '', 0, 3, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (300, 73, 'Data and metadata standards', '', '', '', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (299, 73, 'Types of data produced', '', '', '', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (437, 100, 'Responsibilities and Resources', '', '', '', 0, 7, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (436, 100, 'Data Sharing', '', '', '', 0, 6, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (435, 100, 'Selection and Preservation', '', '', '', 0, 5, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (434, 100, 'Storage and Backup', '', '', '', 0, 4, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (433, 100, 'Ethics and Legal Compliance', '', '', '', 0, 3, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (432, 100, 'Documentation and Metadata', '', '', '', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (431, 100, 'Data Collection', '', '', '', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (311, 59, 256, 'Explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing .
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (310, 59, 255, 'Describe the appropriate use of the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (309, 59, 254, 'State whether an Institutional Review Board (IRB) or analogous review body has reviewed the genomic data sharing aspects of your project, or provide a timeline for such review.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (308, 59, 253, 'Provide a timeline for sharing data in a timely manner.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (307, 59, 252, 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (306, 59, 251, 'Explain whether the research being considered for funding involves human data, non-human data, or both.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (365, 73, 302, 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (364, 73, 301, 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (363, 73, 300, 'Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (362, 73, 299, 'Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (648, 100, 436, 'Are any restrictions on data sharing required?
', '', '
Questions to consider:
Outline any expected difficulties in sharing data with acknowledged long-term value, along with causes and possible measures to overcome these. Restrictions may be due to confidentiality, lack of consent agreements or IPR, for example. Consider whether a non-disclosure agreement would give sufficient protection for confidential data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (649, 100, 437, '
Who will be responsible for data management?
', '', '
Questions to consider:
Outline the roles and responsibilities for all activities e.g. data capture, metadata production, data quality, storage and backup, data archiving and data sharing. Consider who will be responsible for ensuring relevant policies will be respected. Individuals should be named where possible.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (650, 100, 437, '
What resources will you require to deliver your plan?
', '', '
Questions to consider:
Carefully consider any resources needed to deliver the plan, e.g. software, hardware, technical expertise, etc. Where dedicated resources are needed, these should be outlined and justified.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (647, 100, 436, '
How will you share the data?
', '', '
Questions to consider:
Consider where, how, and to whom data with acknowledged long-term value should be made available. The methods used to share data will be dependent on a number of factors such as the type, size, complexity and sensitivity of data. If possible, mention earlier examples to show a track record of effective data sharing. Consider how people might acknowledge the reuse of your data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (646, 100, 435, '
What is the long-term preservation plan for the dataset?
', '', '
Questions to consider:
Consider how datasets that have long-term value will be preserved and curated beyond the lifetime of the grant. Also outline the plans for preparing and documenting data for sharing and archiving. If you do not propose to use an established repository, the data management plan should demonstrate that resources and systems will be in place to enable the data to be curated effectively beyond the lifetime of the grant.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (645, 100, 435, '
Which data are of long-term value and should be retained, shared, and/or preserved?
', '', '
Questions to consider:
Consider how the data may be reused e.g. to validate your research findings, conduct new studies, or for teaching. Decide which data to keep and for how long. This could be based on any obligations to retain certain data, the potential reuse value, what is economically viable to keep, and any additional effort required to prepare the data for data sharing and preservation. Remember to consider any additional effort required to prepare the data for sharing and preservation, such as changing file formats.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (644, 100, 434, '
How will you manage access and security?
', '', '
Questions to consider:
If your data is confidential (e.g. personal data not already in the public domain, confidential information or trade secrets), you should outline any appropriate security measures and note any formal standards that you will comply with e.g. ISO 27001."
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (643, 100, 434, '
How will the data be stored and backed up during the research?
', '', '
Questions to consider:
State how often the data will be backed up and to which locations. How many copies are being made? Storing data on laptops, computer hard drives or external storage devices alone is very risky. The use of robust, managed storage provided by university IT teams is preferable. Similarly, it is normally better to use automatic backup services provided by IT Services than rely on manual processes. If you choose to use a third-party service, you should ensure that this does not conflict with any funder, institutional, departmental or group policies, for example in terms of the legal jurisdiction in which data are held or the protection of sensitive data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (642, 100, 433, '
How will you manage copyright and Intellectual Property Rights (IP/IPR) issues?
', '', '
Questions to consider:
State who will own the copyright and IPR of any data that you will collect or create, along with the licence(s) for its use and reuse. For multi-partner projects, IPR ownership may be worth covering in a consortium agreement. Consider any relevant funder, institutional, departmental or group policies on copyright or IPR. Also consider permissions to reuse third-party data and any restrictions needed on data sharing.
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How will you manage any ethical issues?
', '', '
Questions to consider:
Ethical issues affect how you store data, who can see/use it and how long it is kept. Managing ethical concerns may include: anonymization of data; referral to departmental or institutional ethics committees; and formal consent agreements. You should show that you are aware of any issues and have planned accordingly. If you are carrying out research involving human participants, you must also ensure that consent is requested to allow data to be shared and reused.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (640, 100, 432, '
What documentation and metadata will accompany the data?
', '', '
Questions to consider:
Describe the types of documentation that will accompany the data to help secondary users to understand and reuse it. This should at least include basic details that will help people to find the data, including who created or contributed to the data, its title, date of creation and under what conditions it can be accessed.
Documentation may also include details on the methodology used, analytical and procedural information, definitions of variables, vocabularies, units of measurement, any assumptions made, and the format and file type of the data. Consider how you will capture this information and where it will be recorded. Wherever possible you should identify and use existing community standards.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (639, 100, 431, '
How will the data be collected or created?
', '', '
Questions to consider:
Outline how the data will be collected/created and which community data standards (if any) will be used. Consider how the data will be organized during the project, mentioning for example naming conventions, version control and folder structures. Explain how the consistency and quality of data collection will be controlled and documented. This may include processes such as calibration, repeat samples or measurements, standardized data capture or recording, data entry validation, peer review of data or representation with controlled vocabularies.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (638, 100, 431, '
What data will you collect or create?
', '', '
Questions to consider:
Give a brief description of the data, including any existing data or third-party sources that will be used, in each case noting its content, type and coverage. Outline and justify your choice of format and consider the implications of data format and data volumes in terms of storage, backup and access.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1003, 59, 251, 'wergwertgreg rtghrwt
Explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing .
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (309, 59, 254, 'State whether an Institutional Review Board (IRB) or analogous review body has reviewed the genomic data sharing aspects of your project, or provide a timeline for such review.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (308, 59, 253, 'Provide a timeline for sharing data in a timely manner.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (307, 59, 252, 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (306, 59, 251, 'Explain whether the research being considered for funding involves human data, non-human data, or both.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (365, 73, 302, 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (364, 73, 301, 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (363, 73, 300, 'Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (362, 73, 299, 'Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (648, 100, 436, 'Are any restrictions on data sharing required?
', '', '
Questions to consider:
Outline any expected difficulties in sharing data with acknowledged long-term value, along with causes and possible measures to overcome these. Restrictions may be due to confidentiality, lack of consent agreements or IPR, for example. Consider whether a non-disclosure agreement would give sufficient protection for confidential data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (649, 100, 437, '
Who will be responsible for data management?
', '', '
Questions to consider:
Outline the roles and responsibilities for all activities e.g. data capture, metadata production, data quality, storage and backup, data archiving and data sharing. Consider who will be responsible for ensuring relevant policies will be respected. Individuals should be named where possible.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (650, 100, 437, '
What resources will you require to deliver your plan?
', '', '
Questions to consider:
Carefully consider any resources needed to deliver the plan, e.g. software, hardware, technical expertise, etc. Where dedicated resources are needed, these should be outlined and justified.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (647, 100, 436, '
How will you share the data?
', '', '
Questions to consider:
Consider where, how, and to whom data with acknowledged long-term value should be made available. The methods used to share data will be dependent on a number of factors such as the type, size, complexity and sensitivity of data. If possible, mention earlier examples to show a track record of effective data sharing. Consider how people might acknowledge the reuse of your data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (646, 100, 435, '
What is the long-term preservation plan for the dataset?
', '', '
Questions to consider:
Consider how datasets that have long-term value will be preserved and curated beyond the lifetime of the grant. Also outline the plans for preparing and documenting data for sharing and archiving. If you do not propose to use an established repository, the data management plan should demonstrate that resources and systems will be in place to enable the data to be curated effectively beyond the lifetime of the grant.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (645, 100, 435, '
Which data are of long-term value and should be retained, shared, and/or preserved?
', '', '
Questions to consider:
Consider how the data may be reused e.g. to validate your research findings, conduct new studies, or for teaching. Decide which data to keep and for how long. This could be based on any obligations to retain certain data, the potential reuse value, what is economically viable to keep, and any additional effort required to prepare the data for data sharing and preservation. Remember to consider any additional effort required to prepare the data for sharing and preservation, such as changing file formats.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (644, 100, 434, '
How will you manage access and security?
', '', '
Questions to consider:
If your data is confidential (e.g. personal data not already in the public domain, confidential information or trade secrets), you should outline any appropriate security measures and note any formal standards that you will comply with e.g. ISO 27001."
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (643, 100, 434, '
How will the data be stored and backed up during the research?
', '', '
Questions to consider:
State how often the data will be backed up and to which locations. How many copies are being made? Storing data on laptops, computer hard drives or external storage devices alone is very risky. The use of robust, managed storage provided by university IT teams is preferable. Similarly, it is normally better to use automatic backup services provided by IT Services than rely on manual processes. If you choose to use a third-party service, you should ensure that this does not conflict with any funder, institutional, departmental or group policies, for example in terms of the legal jurisdiction in which data are held or the protection of sensitive data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (642, 100, 433, '
How will you manage copyright and Intellectual Property Rights (IP/IPR) issues?
', '', '
Questions to consider:
State who will own the copyright and IPR of any data that you will collect or create, along with the licence(s) for its use and reuse. For multi-partner projects, IPR ownership may be worth covering in a consortium agreement. Consider any relevant funder, institutional, departmental or group policies on copyright or IPR. Also consider permissions to reuse third-party data and any restrictions needed on data sharing.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (641, 100, 433, '
How will you manage any ethical issues?
', '', '
Questions to consider:
Ethical issues affect how you store data, who can see/use it and how long it is kept. Managing ethical concerns may include: anonymization of data; referral to departmental or institutional ethics committees; and formal consent agreements. You should show that you are aware of any issues and have planned accordingly. If you are carrying out research involving human participants, you must also ensure that consent is requested to allow data to be shared and reused.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (640, 100, 432, '
What documentation and metadata will accompany the data?
', '', '
Questions to consider:
Describe the types of documentation that will accompany the data to help secondary users to understand and reuse it. This should at least include basic details that will help people to find the data, including who created or contributed to the data, its title, date of creation and under what conditions it can be accessed.
Documentation may also include details on the methodology used, analytical and procedural information, definitions of variables, vocabularies, units of measurement, any assumptions made, and the format and file type of the data. Consider how you will capture this information and where it will be recorded. Wherever possible you should identify and use existing community standards.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (639, 100, 431, '
How will the data be collected or created?
', '', '
Questions to consider:
Outline how the data will be collected/created and which community data standards (if any) will be used. Consider how the data will be organized during the project, mentioning for example naming conventions, version control and folder structures. Explain how the consistency and quality of data collection will be controlled and documented. This may include processes such as calibration, repeat samples or measurements, standardized data capture or recording, data entry validation, peer review of data or representation with controlled vocabularies.
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What data will you collect or create?
', '', '
Questions to consider:
Give a brief description of the data, including any existing data or third-party sources that will be used, in each case noting its content, type and coverage. Outline and justify your choice of format and consider the implications of data format and data volumes in terms of storage, backup and access.
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NSF Generic - informal review
http://www.dcc.ac.uk/resources/how-guides/develop-data-plan
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http://www.dcc.ac.uk/resources/how-guides/develop-data-plan
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Outline volume, type, content, quality and format of the final dataset Outline the metadata, documentation or other supporting material that should accompany the data for it to be interpreted correctly. What standards and methodologies will be utilised for data collection and management? State the relationship to other data available in public repositories e.g. existing data sources that will be used by the research project; gaps between available data and that required for the research; the added value that new data would provide in relation to existing data.
', '', 'Outline and justify your choices: You should detail what data you will create and explain why you have opted for particular formats, standards and methodologies. Bear in mind that the choices you make may make it easier or harder to share and preserve your data.
It can be useful to capture your data in (or convert it to) community-accepted data formats. Using standard or widely-adopted formats will make your data interoperable. Open or non-proprietary formats are preferable, as you and others will have less trouble processing these later. If your data are to be deposited into an archive, particular formats may be preferred.
Documentation and metadata allow your data to be understood and discovered by others. It is fundamental to capture contextual details about how and why the data were created. Metadata is a subset of this broad documentation, describing the data in detail. There are various metadata standards which can help you to describe your data in a consistent way. Librarians, data repositories or your colleagues may be able to advise on relevant standards.
Make informed decision based on review: It can help to show your awareness of good practice or that you have sought advice to develop your plans. Some funders also expect you to demonstrate that existing data are not sufficient for your needs, so you may need to show that you have reviewed repository and data centre holdings or consulted with similar projects.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (322, 59, 288, 640, 'Example funder prompts: Demonstrate that you have sought advice on and addressed all copyright and rights management issues that apply to the resource. Make explicit mention of consent, confidentiality, anonymisation and other ethical considerations, where appropriate. Are any restrictions on data sharing required – for example to safeguard research participants or to gain appropriate intellectual property protection?
', '', 'Present a strong case for any restrictions on sharing: Explain any constraints, such as embargo periods or restricted access, and ensure these are properly justified as there is a common expectation that publicly funded research data will be openly available as soon as possible. These justifications may also be of use in the event of a Freedom of Information request for your research data.
All research involving human data or material is subject to formal ethical review. Where appropriate, you should outline the steps you will take to protect research participants, e.g. anonymising data. It helps to show that you’ve balanced concerns with the desire to share e.g. by negotiating informed consent for data sharing. Many University Ethics Committees provide sample consent forms and services such as the UK Data Archive provide excellent guidance in this area. You should also demonstrate awareness of relevant legislation such as the Data Protection Act.
Data ownership should be clarified and, where necessary, plans should be in place to negotiate licences at the start of the research process. If you agree/purchase licences to reuse third party data, be aware of any restrictions this places on subsequent deposit and data sharing. JISC Legal provides lots of advice on copyright, IPR and relevant legislation such as the Data Protection Act and Freedom of Information. Institutional support is also available from experts in university libraries, records management and research offices.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (323, 59, 289, 641, 'Example funder prompts: What are the further intended and/or foreseeable research uses for the completed dataset(s)? How you will make the resource accessible to the potential audience(s) identified? Where will you make the data available? How will other researchers be able to access the data? Will a data sharing agreement be required? What is the timescale for public release of the data? State any expected difficulties in data sharing, along with causes and possible measures to overcome these difficulties. How will data sharing provide opportunities for coordination or collaboration?
', '', 'Anticipate and plan for data reuse: It can help to envisage which users your data would be of value to, and address their needs when deciding how to make the data available. Data centres may also ask you to meet minimum quality standards to make sure your data can be understood and reused by other researchers.
Provide specific details on access: Reassure funders by being very clear about where, when and how your data will be made available. The DCC offers guidance on how to licence your data to make clear who can use it and for what purpose. Funders often state expected timeframes for release, such as making data available on publication. If you can’t meet these expectations or need to impose any restrictions, try to demonstrate that you have considered various means of overcoming these challenges.
Use existing infrastructure: Where possible select an appropriate disciplinary database, data centre or institutional repository. If you are unsure which services are available to you, check the repository list collated by DataCite, BioMed Central and the DCC. If access to your data needs to be restricted, look for secure data services or data enclaves.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (324, 59, 290, 643, 'Example funder prompts: Describe the planned quality assurance and back-up procedures [security/storage]. Specify the responsibilities for data management and curation within research teams at all participating institutions.
', '', 'Define data management support: Outline what provision is available to you within your institution and any additional skills or resources that you need to secure. If local support is available, it helps to demonstrate that you have discussed and agreed requirements. If you need to secure external support, justify the selections made and budget requested. Be clear about who will be responsible for different tasks.
Consider the practicalities: Are the investigators co-located, or will you need infrastructure that accommodates secure remote access? How will data quality be monitored if you are working in a distributed network across several sites? Strong file-naming conventions and versioning applications may be of use to keep track of the development process, particularly when several people are working together.
Apply appropriate levels of data management: Funders want to be reassured that the day-to-day data management is fit for purpose. You may apply differing levels of service or adopt a combination of approaches:
Example funder prompts: Identify which of the data sets produced are considered to be of long-term value. Outline the plans for preparing and documenting data for preservation and sharing. Explain your archiving/preservation plan to ensure the long-term value of key datasets.
', '', 'Select data of long-term value: Data sharing and preservation may not be applicable in every case. The DCC provides a ‘How to …’ guide on appraisal, which offers practical strategies to help you select important data. Deciding what has long-term value and preparing those data to expected standards for deposit are time-consuming processes, for which you should allocate significant resources.
Safeguard the data behind the graph: It is a common expectation among RCUK funders that published results will include information on how to access the supporting data. Even if there is no obvious home for the majority of your data, the data which underpin publications should be extracted, captured in machine-readable form and deposited somewhere so they remain accessible.
Assure that your data will remain accessible: Whatever approach you adopt, focus on making a convincing case that your data will remain accessible. If you plan to deposit in a data centre, it helps to speak with their staff early on as they can advise what is appropriate and feasible in terms of preservation. Universities are increasingly providing infrastructure to support data management and there are some disciplinary services which may be of use.
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', '', 'Outline and justify costs: If you need to purchase storage, outsource services such as back-up and preservation, or plan to pay for data management support, these costs should be outlined and justified in your proposal. Where institutional provision is available, show that the support you require has been discussed and agreed. It also helps to link resources with roles and responsibilities to demonstrate how the plan will be implemented.
Don’t underestimate the human effort required: Creating documentation and making your data understandable to others is very time consuming, so be realistic about how much effort is needed to prepare your data for sharing and preservation. The UKDA offers a toolkit to help researchers cost activities related to managing and sharing social science data.
Show efficient use of public funds: The RCUK Common Principles on Data Policy state that it is appropriate to use public funds to support the management and sharing of publicly-funded research data, but this is expected to be efficient and cost-effective. A summary of individual funder’s views on meeting associated costs is available via the DCC policy pages.
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (546, 101, 459, 308, 'Provide a timeline for sharing data in a timely manner.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (545, 101, 458, 307, 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (544, 101, 457, 306, 'Explain whether the research being considered for funding involves human data, non-human data, or both.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (865, 123, 591, 365, 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (864, 123, 590, 364, 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (863, 123, 589, 363, 'Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (862, 123, 588, 362, 'Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (951, 140, 666, 638, 'Example funder prompts: What data outputs will your research generate? Outline volume, type, content, quality and format of the final dataset Outline the metadata, documentation or other supporting material that should accompany the data for it to be interpreted correctly. What standards and methodologies will be utilised for data collection and management? State the relationship to other data available in public repositories e.g. existing data sources that will be used by the research project; gaps between available data and that required for the research; the added value that new data would provide in relation to existing data.
', '', 'Guidance for data types:
Outline and justify your choices: You should detail what data you will create and explain why you have opted for particular formats, standards and methodologies. Bear in mind that the choices you make may make it easier or harder to share and preserve your data.
It can be useful to capture your data in (or convert it to) community-accepted data formats. Using standard or widely-adopted formats will make your data interoperable. Open or non-proprietary formats are preferable, as you and others will have less trouble processing these later. If your data are to be deposited into an archive, particular formats may be preferred.
Documentation and metadata allow your data to be understood and discovered by others. It is fundamental to capture contextual details about how and why the data were created. Metadata is a subset of this broad documentation, describing the data in detail. There are various metadata standards which can help you to describe your data in a
DCC: How to Develop a DMP
Example funder prompts: Demonstrate that you have sought advice on and addressed all copyright and rights management issues that apply to the resource. Make explicit mention of consent, confidentiality, anonymisation and other ethical considerations, where appropriate. Are any restrictions on data sharing required – for example to safeguard research participants or to gain appropriate intellectual property protection?
', '', 'Guidance for ethics:
Present a strong case for any restrictions on sharing: Explain any constraints, such as embargo periods or restricted access, and ensure these are properly justified as there is a common expectation that publicly funded research data will be openly available as soon as possible. These justifications may also be of use in the event of a Freedom of Information request for your research data.
All research involving human data or material is subject to formal ethical review. Where appropriate, you should outline the steps you will take to protect research participants, e.g. anonymising data. It helps to show that you’ve balanced concerns with the desire to share e.g. by negotiating informed consent for data sharing. Many University Ethics Committees provide sample consent forms and services such as the UK Data Archive provide excellent guidance in this area. You should also demonstrate awareness of relevant legislation such as the Data Protection Act.
Data ownersh
DCC: How to Develop a DMP
Example funder prompts: What are the further intended and/or foreseeable research uses for the completed dataset(s)? How you will make the resource accessible to the potential audience(s) identified? Where will you make the data available? How will other researchers be able to access the data? Will a data sharing agreement be required? What is the timescale for public release of the data? State any expected difficulties in data sharing, along with causes and possible measures to overcome these difficulties. How will data sharing provide opportunities for coordination or collaboration?
', '', 'Guidance for reuse:
Anticipate and plan for data reuse: It can help to envisage which users your data would be of value to, and address their needs when deciding how to make the data available. Data centres may also ask you to meet minimum quality standards to make sure your data can be understood and reused by other researchers.
Provide specific details on access: Reassure funders by being very clear about where, when and how your data will be made available. The DCC offers guidance on how to licence your data to make clear who can use it and for what purpose. Funders often state expected timeframes for release, such as making data available on publication. If you can’t meet these expectations or need to impose any restrictions, try to demonstrate that you have considered various means of overcoming these challenges.
Use existing infrastructure: Where possible select an appropriate disciplinary database, data centre or institutional repository. If you are unsure which services a
DCC: How to Develop a DMP
Example funder prompts: Describe the planned quality assurance and back-up procedures [security/storage]. Specify the responsibilities for data management and curation within research teams at all participating institutions.
', '', 'Guidance for short-term storage:
Define data management support: Outline what provision is available to you within your institution and any additional skills or resources that you need to secure. If local support is available, it helps to demonstrate that you have discussed and agreed requirements. If you need to secure external support, justify the selections made and budget requested. Be clear about who will be responsible for different tasks.
Consider the practicalities: Are the investigators co-located, or will you need infrastructure that accommodates secure remote access? How will data quality be monitored if you are working in a distributed network across several sites? Strong file-naming conventions and versioning applications may be of use to keep track of the development process, particularly when several people are working together.
Apply appropriate levels of data management: Funders want to be reassured that the day-to-day data management is fit for purpose. You may ap
DCC: How to Develop a DMP
Example funder prompts: Identify which of the data sets produced are considered to be of long-term value. Outline the plans for preparing and documenting data for preservation and sharing. Explain your archiving/preservation plan to ensure the long-term value of key datasets.
', '', 'Guidance for deposit:
Select data of long-term value: Data sharing and preservation may not be applicable in every case. The DCC provides a ‘How to …’ guide on appraisal, which offers practical strategies to help you select important data. Deciding what has long-term value and preparing those data to expected standards for deposit are time-consuming processes, for which you should allocate significant resources.
Safeguard the data behind the graph: It is a common expectation among RCUK funders that published results will include information on how to access the supporting data. Even if there is no obvious home for the majority of your data, the data which underpin publications should be extracted, captured in machine-readable form and deposited somewhere so they remain accessible.
Assure that your data will remain accessible: Whatever approach you adopt, focus on making a convincing case that your data will remain accessible. If you plan to deposit in a data centre, it helps t
DCC: How to Develop a DMP
Example prompts: What resources will you require to deliver your plan? Outline additional hardware, software and technical expertise, support and training that is likely to be required and how it will be acquired.
', '', 'Guidance on resourcing:
Outline and justify costs: If you need to purchase storage, outsource services such as back-up and preservation, or plan to pay for data management support, these costs should be outlined and justified in your proposal. Where institutional provision is available, show that the support you require has been discussed and agreed. It also helps to link resources with roles and responsibilities to demonstrate how the plan will be implemented.
Don’t underestimate the human effort required: Creating documentation and making your data understandable to others is very time consuming, so be realistic about how much effort is needed to prepare your data for sharing and preservation. The UKDA offers a toolkit to help researchers cost activities related to managing and sharing social science data.
Show efficient use of public funds: The RCUK Common Principles on Data Policy state that it is appropriate to use public funds to support the management and sharing of publicl
DCC: How to Develop a DMP
What data will you collect or create?
', '', '
Questions to consider:
Give a brief description of the data, including any existing data or third-party sources that will be used, in each case noting its content, type and coverage. Outline and justify your choice of format and consider the implications of data format and data volumes in terms of storage, backup and access.
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How will the data be collected or created?
', '', '
Questions to consider:
Outline how the data will be collected/created and which community data standards (if any) will be used. Consider how the data will be organized during the project, mentioning for example naming conventions, version control and folder structures. Explain how the consistency and quality of data collection will be controlled and documented. This may include processes such as calibration, repeat samples or measurements, standardized data capture or recording, data entry validation, peer review of data or representation with controlled vocabularies.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2494, 238, 1329, 640, '
What documentation and metadata will accompany the data?
', '', '
Questions to consider:
Describe the types of documentation that will accompany the data to help secondary users to understand and reuse it. This should at least include basic details that will help people to find the data, including who created or contributed to the data, its title, date of creation and under what conditions it can be accessed.
Documentation may also include details on the methodology used, analytical and procedural information, definitions of variables, vocabularies, units of measurement, any assumptions made, and the format and file type of the data. Consider how you will capture this information and where it will be recorded. Wherever possible you should identify and use existing community standards.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2495, 238, 1330, 641, '
How will you manage any ethical issues?
', '', '
Questions to consider:
Ethical issues affect how you store data, who can see/use it and how long it is kept. Managing ethical concerns may include: anonymization of data; referral to departmental or institutional ethics committees; and formal consent agreements. You should show that you are aware of any issues and have planned accordingly. If you are carrying out research involving human participants, you must also ensure that consent is requested to allow data to be shared and reused.
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How will you manage copyright and Intellectual Property Rights (IP/IPR) issues?
', '', '
Questions to consider:
State who will own the copyright and IPR of any data that you will collect or create, along with the licence(s) for its use and reuse. For multi-partner projects, IPR ownership may be worth covering in a consortium agreement. Consider any relevant funder, institutional, departmental or group policies on copyright or IPR. Also consider permissions to reuse third-party data and any restrictions needed on data sharing.
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How will the data be stored and backed up during the research?
', '', '
Questions to consider:
State how often the data will be backed up and to which locations. How many copies are being made? Storing data on laptops, computer hard drives or external storage devices alone is very risky. The use of robust, managed storage provided by university IT teams is preferable. Similarly, it is normally better to use automatic backup services provided by IT Services than rely on manual processes. If you choose to use a third-party service, you should ensure that this does not conflict with any funder, institutional, departmental or group policies, for example in terms of the legal jurisdiction in which data are held or the protection of sensitive data.
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How will you manage access and security?
', '', '
Questions to consider:
If your data is confidential (e.g. personal data not already in the public domain, confidential information or trade secrets), you should outline any appropriate security measures and note any formal standards that you will comply with e.g. ISO 27001."
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2499, 238, 1332, 645, '
Which data are of long-term value and should be retained, shared, and/or preserved?
', '', '
Questions to consider:
Consider how the data may be reused e.g. to validate your research findings, conduct new studies, or for teaching. Decide which data to keep and for how long. This could be based on any obligations to retain certain data, the potential reuse value, what is economically viable to keep, and any additional effort required to prepare the data for data sharing and preservation. Remember to consider any additional effort required to prepare the data for sharing and preservation, such as changing file formats.
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What is the long-term preservation plan for the dataset?
', '', '
Questions to consider:
Consider how datasets that have long-term value will be preserved and curated beyond the lifetime of the grant. Also outline the plans for preparing and documenting data for sharing and archiving. If you do not propose to use an established repository, the data management plan should demonstrate that resources and systems will be in place to enable the data to be curated effectively beyond the lifetime of the grant.
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How will you share the data?
', '', '
Questions to consider:
Consider where, how, and to whom data with acknowledged long-term value should be made available. The methods used to share data will be dependent on a number of factors such as the type, size, complexity and sensitivity of data. If possible, mention earlier examples to show a track record of effective data sharing. Consider how people might acknowledge the reuse of your data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2502, 238, 1333, 648, '
Are any restrictions on data sharing required?
', '', '
Questions to consider:
Outline any expected difficulties in sharing data with acknowledged long-term value, along with causes and possible measures to overcome these. Restrictions may be due to confidentiality, lack of consent agreements or IPR, for example. Consider whether a non-disclosure agreement would give sufficient protection for confidential data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2503, 238, 1460, 649, '
Who will be responsible for data management?
', '', '
Questions to consider:
Outline the roles and responsibilities for all activities e.g. data capture, metadata production, data quality, storage and backup, data archiving and data sharing. Consider who will be responsible for ensuring relevant policies will be respected. Individuals should be named where possible.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2504, 238, 1460, 650, '
What resources will you require to deliver your plan?
', '', '
Questions to consider:
Carefully consider any resources needed to deliver the plan, e.g. software, hardware, technical expertise, etc. Where dedicated resources are needed, these should be outlined and justified.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, CURDATE(), @default_admin_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3395, 101, 457, 1003, 'wergwertgreg rtghrwt
Example funder prompts: What data outputs will your research generate? Outline volume, type, content, quality and format of the final dataset Outline the metadata, documentation or other supporting material that should accompany the data for it to be interpreted correctly. What standards and methodologies will be utilised for data collection and management? State the relationship to other data available in public repositories e.g. existing data sources that will be used by the research project; gaps between available data and that required for the research; the added value that new data would provide in relation to existing data.
', '', 'Outline and justify your choices: You should detail what data you will create and explain why you have opted for particular formats, standards and methodologies. Bear in mind that the choices you make may make it easier or harder to share and preserve your data.
It can be useful to capture your data in (or convert it to) community-accepted data formats. Using standard or widely-adopted formats will make your data interoperable. Open or non-proprietary formats are preferable, as you and others will have less trouble processing these later. If your data are to be deposited into an archive, particular formats may be preferred.
Documentation and metadata allow your data to be understood and discovered by others. It is fundamental to capture contextual details about how and why the data were created. Metadata is a subset of this broad documentation, describing the data in detail. There are various metadata standards which can help you to describe your data in a consistent way. Librarians, data repositories or your colleagues may be able to advise on relevant standards.
Make informed decision based on review: It can help to show your awareness of good practice or that you have sought advice to develop your plans. Some funders also expect you to demonstrate that existing data are not sufficient for your needs, so you may need to show that you have reviewed repository and data centre holdings or consulted with similar projects.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (322, 59, 288, 640, 'Example funder prompts: Demonstrate that you have sought advice on and addressed all copyright and rights management issues that apply to the resource. Make explicit mention of consent, confidentiality, anonymisation and other ethical considerations, where appropriate. Are any restrictions on data sharing required – for example to safeguard research participants or to gain appropriate intellectual property protection?
', '', 'Present a strong case for any restrictions on sharing: Explain any constraints, such as embargo periods or restricted access, and ensure these are properly justified as there is a common expectation that publicly funded research data will be openly available as soon as possible. These justifications may also be of use in the event of a Freedom of Information request for your research data.
All research involving human data or material is subject to formal ethical review. Where appropriate, you should outline the steps you will take to protect research participants, e.g. anonymising data. It helps to show that you’ve balanced concerns with the desire to share e.g. by negotiating informed consent for data sharing. Many University Ethics Committees provide sample consent forms and services such as the UK Data Archive provide excellent guidance in this area. You should also demonstrate awareness of relevant legislation such as the Data Protection Act.
Data ownership should be clarified and, where necessary, plans should be in place to negotiate licences at the start of the research process. If you agree/purchase licences to reuse third party data, be aware of any restrictions this places on subsequent deposit and data sharing. JISC Legal provides lots of advice on copyright, IPR and relevant legislation such as the Data Protection Act and Freedom of Information. Institutional support is also available from experts in university libraries, records management and research offices.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (323, 59, 289, 641, 'Example funder prompts: What are the further intended and/or foreseeable research uses for the completed dataset(s)? How you will make the resource accessible to the potential audience(s) identified? Where will you make the data available? How will other researchers be able to access the data? Will a data sharing agreement be required? What is the timescale for public release of the data? State any expected difficulties in data sharing, along with causes and possible measures to overcome these difficulties. How will data sharing provide opportunities for coordination or collaboration?
', '', 'Anticipate and plan for data reuse: It can help to envisage which users your data would be of value to, and address their needs when deciding how to make the data available. Data centres may also ask you to meet minimum quality standards to make sure your data can be understood and reused by other researchers.
Provide specific details on access: Reassure funders by being very clear about where, when and how your data will be made available. The DCC offers guidance on how to licence your data to make clear who can use it and for what purpose. Funders often state expected timeframes for release, such as making data available on publication. If you can’t meet these expectations or need to impose any restrictions, try to demonstrate that you have considered various means of overcoming these challenges.
Use existing infrastructure: Where possible select an appropriate disciplinary database, data centre or institutional repository. If you are unsure which services are available to you, check the repository list collated by DataCite, BioMed Central and the DCC. If access to your data needs to be restricted, look for secure data services or data enclaves.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (324, 59, 290, 643, 'Example funder prompts: Describe the planned quality assurance and back-up procedures [security/storage]. Specify the responsibilities for data management and curation within research teams at all participating institutions.
', '', 'Define data management support: Outline what provision is available to you within your institution and any additional skills or resources that you need to secure. If local support is available, it helps to demonstrate that you have discussed and agreed requirements. If you need to secure external support, justify the selections made and budget requested. Be clear about who will be responsible for different tasks.
Consider the practicalities: Are the investigators co-located, or will you need infrastructure that accommodates secure remote access? How will data quality be monitored if you are working in a distributed network across several sites? Strong file-naming conventions and versioning applications may be of use to keep track of the development process, particularly when several people are working together.
Apply appropriate levels of data management: Funders want to be reassured that the day-to-day data management is fit for purpose. You may apply differing levels of service or adopt a combination of approaches:
Example funder prompts: Identify which of the data sets produced are considered to be of long-term value. Outline the plans for preparing and documenting data for preservation and sharing. Explain your archiving/preservation plan to ensure the long-term value of key datasets.
', '', 'Select data of long-term value: Data sharing and preservation may not be applicable in every case. The DCC provides a ‘How to …’ guide on appraisal, which offers practical strategies to help you select important data. Deciding what has long-term value and preparing those data to expected standards for deposit are time-consuming processes, for which you should allocate significant resources.
Safeguard the data behind the graph: It is a common expectation among RCUK funders that published results will include information on how to access the supporting data. Even if there is no obvious home for the majority of your data, the data which underpin publications should be extracted, captured in machine-readable form and deposited somewhere so they remain accessible.
Assure that your data will remain accessible: Whatever approach you adopt, focus on making a convincing case that your data will remain accessible. If you plan to deposit in a data centre, it helps to speak with their staff early on as they can advise what is appropriate and feasible in terms of preservation. Universities are increasingly providing infrastructure to support data management and there are some disciplinary services which may be of use.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (326, 59, 292, 647, 'Example prompts: What resources will you require to deliver your plan? Outline additional hardware, software and technical expertise, support and training that is likely to be required and how it will be acquired.
', '', 'Outline and justify costs: If you need to purchase storage, outsource services such as back-up and preservation, or plan to pay for data management support, these costs should be outlined and justified in your proposal. Where institutional provision is available, show that the support you require has been discussed and agreed. It also helps to link resources with roles and responsibilities to demonstrate how the plan will be implemented.
Don’t underestimate the human effort required: Creating documentation and making your data understandable to others is very time consuming, so be realistic about how much effort is needed to prepare your data for sharing and preservation. The UKDA offers a toolkit to help researchers cost activities related to managing and sharing social science data.
Show efficient use of public funds: The RCUK Common Principles on Data Policy state that it is appropriate to use public funds to support the management and sharing of publicly-funded research data, but this is expected to be efficient and cost-effective. A summary of individual funder’s views on meeting associated costs is available via the DCC policy pages.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (549, 101, 462, 311, 'Explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing .
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (548, 101, 461, 310, 'Describe the appropriate use of the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (547, 101, 460, 309, 'State whether an Institutional Review Board (IRB) or analogous review body has reviewed the genomic data sharing aspects of your project, or provide a timeline for such review.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (546, 101, 459, 308, 'Provide a timeline for sharing data in a timely manner.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (545, 101, 458, 307, 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (544, 101, 457, 306, 'Explain whether the research being considered for funding involves human data, non-human data, or both.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (865, 123, 591, 365, 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (864, 123, 590, 364, 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (863, 123, 589, 363, 'Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (862, 123, 588, 362, 'Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (951, 140, 666, 638, 'Example funder prompts: What data outputs will your research generate? Outline volume, type, content, quality and format of the final dataset Outline the metadata, documentation or other supporting material that should accompany the data for it to be interpreted correctly. What standards and methodologies will be utilised for data collection and management? State the relationship to other data available in public repositories e.g. existing data sources that will be used by the research project; gaps between available data and that required for the research; the added value that new data would provide in relation to existing data.
', '', 'Guidance for data types:
Outline and justify your choices: You should detail what data you will create and explain why you have opted for particular formats, standards and methodologies. Bear in mind that the choices you make may make it easier or harder to share and preserve your data.
It can be useful to capture your data in (or convert it to) community-accepted data formats. Using standard or widely-adopted formats will make your data interoperable. Open or non-proprietary formats are preferable, as you and others will have less trouble processing these later. If your data are to be deposited into an archive, particular formats may be preferred.
Documentation and metadata allow your data to be understood and discovered by others. It is fundamental to capture contextual details about how and why the data were created. Metadata is a subset of this broad documentation, describing the data in detail. There are various metadata standards which can help you to describe your data in a
DCC: How to Develop a DMP
Example funder prompts: Demonstrate that you have sought advice on and addressed all copyright and rights management issues that apply to the resource. Make explicit mention of consent, confidentiality, anonymisation and other ethical considerations, where appropriate. Are any restrictions on data sharing required – for example to safeguard research participants or to gain appropriate intellectual property protection?
', '', 'Guidance for ethics:
Present a strong case for any restrictions on sharing: Explain any constraints, such as embargo periods or restricted access, and ensure these are properly justified as there is a common expectation that publicly funded research data will be openly available as soon as possible. These justifications may also be of use in the event of a Freedom of Information request for your research data.
All research involving human data or material is subject to formal ethical review. Where appropriate, you should outline the steps you will take to protect research participants, e.g. anonymising data. It helps to show that you’ve balanced concerns with the desire to share e.g. by negotiating informed consent for data sharing. Many University Ethics Committees provide sample consent forms and services such as the UK Data Archive provide excellent guidance in this area. You should also demonstrate awareness of relevant legislation such as the Data Protection Act.
Data ownersh
DCC: How to Develop a DMP
Example funder prompts: What are the further intended and/or foreseeable research uses for the completed dataset(s)? How you will make the resource accessible to the potential audience(s) identified? Where will you make the data available? How will other researchers be able to access the data? Will a data sharing agreement be required? What is the timescale for public release of the data? State any expected difficulties in data sharing, along with causes and possible measures to overcome these difficulties. How will data sharing provide opportunities for coordination or collaboration?
', '', 'Guidance for reuse:
Anticipate and plan for data reuse: It can help to envisage which users your data would be of value to, and address their needs when deciding how to make the data available. Data centres may also ask you to meet minimum quality standards to make sure your data can be understood and reused by other researchers.
Provide specific details on access: Reassure funders by being very clear about where, when and how your data will be made available. The DCC offers guidance on how to licence your data to make clear who can use it and for what purpose. Funders often state expected timeframes for release, such as making data available on publication. If you can’t meet these expectations or need to impose any restrictions, try to demonstrate that you have considered various means of overcoming these challenges.
Use existing infrastructure: Where possible select an appropriate disciplinary database, data centre or institutional repository. If you are unsure which services a
DCC: How to Develop a DMP
Example funder prompts: Describe the planned quality assurance and back-up procedures [security/storage]. Specify the responsibilities for data management and curation within research teams at all participating institutions.
', '', 'Guidance for short-term storage:
Define data management support: Outline what provision is available to you within your institution and any additional skills or resources that you need to secure. If local support is available, it helps to demonstrate that you have discussed and agreed requirements. If you need to secure external support, justify the selections made and budget requested. Be clear about who will be responsible for different tasks.
Consider the practicalities: Are the investigators co-located, or will you need infrastructure that accommodates secure remote access? How will data quality be monitored if you are working in a distributed network across several sites? Strong file-naming conventions and versioning applications may be of use to keep track of the development process, particularly when several people are working together.
Apply appropriate levels of data management: Funders want to be reassured that the day-to-day data management is fit for purpose. You may ap
DCC: How to Develop a DMP
Example funder prompts: Identify which of the data sets produced are considered to be of long-term value. Outline the plans for preparing and documenting data for preservation and sharing. Explain your archiving/preservation plan to ensure the long-term value of key datasets.
', '', 'Guidance for deposit:
Select data of long-term value: Data sharing and preservation may not be applicable in every case. The DCC provides a ‘How to …’ guide on appraisal, which offers practical strategies to help you select important data. Deciding what has long-term value and preparing those data to expected standards for deposit are time-consuming processes, for which you should allocate significant resources.
Safeguard the data behind the graph: It is a common expectation among RCUK funders that published results will include information on how to access the supporting data. Even if there is no obvious home for the majority of your data, the data which underpin publications should be extracted, captured in machine-readable form and deposited somewhere so they remain accessible.
Assure that your data will remain accessible: Whatever approach you adopt, focus on making a convincing case that your data will remain accessible. If you plan to deposit in a data centre, it helps t
DCC: How to Develop a DMP
Example prompts: What resources will you require to deliver your plan? Outline additional hardware, software and technical expertise, support and training that is likely to be required and how it will be acquired.
', '', 'Guidance on resourcing:
Outline and justify costs: If you need to purchase storage, outsource services such as back-up and preservation, or plan to pay for data management support, these costs should be outlined and justified in your proposal. Where institutional provision is available, show that the support you require has been discussed and agreed. It also helps to link resources with roles and responsibilities to demonstrate how the plan will be implemented.
Don’t underestimate the human effort required: Creating documentation and making your data understandable to others is very time consuming, so be realistic about how much effort is needed to prepare your data for sharing and preservation. The UKDA offers a toolkit to help researchers cost activities related to managing and sharing social science data.
Show efficient use of public funds: The RCUK Common Principles on Data Policy state that it is appropriate to use public funds to support the management and sharing of publicl
DCC: How to Develop a DMP
What data will you collect or create?
', '', '
Questions to consider:
Give a brief description of the data, including any existing data or third-party sources that will be used, in each case noting its content, type and coverage. Outline and justify your choice of format and consider the implications of data format and data volumes in terms of storage, backup and access.
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How will the data be collected or created?
', '', '
Questions to consider:
Outline how the data will be collected/created and which community data standards (if any) will be used. Consider how the data will be organized during the project, mentioning for example naming conventions, version control and folder structures. Explain how the consistency and quality of data collection will be controlled and documented. This may include processes such as calibration, repeat samples or measurements, standardized data capture or recording, data entry validation, peer review of data or representation with controlled vocabularies.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2494, 238, 1329, 640, '
What documentation and metadata will accompany the data?
', '', '
Questions to consider:
Describe the types of documentation that will accompany the data to help secondary users to understand and reuse it. This should at least include basic details that will help people to find the data, including who created or contributed to the data, its title, date of creation and under what conditions it can be accessed.
Documentation may also include details on the methodology used, analytical and procedural information, definitions of variables, vocabularies, units of measurement, any assumptions made, and the format and file type of the data. Consider how you will capture this information and where it will be recorded. Wherever possible you should identify and use existing community standards.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2495, 238, 1330, 641, '
How will you manage any ethical issues?
', '', '
Questions to consider:
Ethical issues affect how you store data, who can see/use it and how long it is kept. Managing ethical concerns may include: anonymization of data; referral to departmental or institutional ethics committees; and formal consent agreements. You should show that you are aware of any issues and have planned accordingly. If you are carrying out research involving human participants, you must also ensure that consent is requested to allow data to be shared and reused.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2496, 238, 1330, 642, '
How will you manage copyright and Intellectual Property Rights (IP/IPR) issues?
', '', '
Questions to consider:
State who will own the copyright and IPR of any data that you will collect or create, along with the licence(s) for its use and reuse. For multi-partner projects, IPR ownership may be worth covering in a consortium agreement. Consider any relevant funder, institutional, departmental or group policies on copyright or IPR. Also consider permissions to reuse third-party data and any restrictions needed on data sharing.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2497, 238, 1331, 643, '
How will the data be stored and backed up during the research?
', '', '
Questions to consider:
State how often the data will be backed up and to which locations. How many copies are being made? Storing data on laptops, computer hard drives or external storage devices alone is very risky. The use of robust, managed storage provided by university IT teams is preferable. Similarly, it is normally better to use automatic backup services provided by IT Services than rely on manual processes. If you choose to use a third-party service, you should ensure that this does not conflict with any funder, institutional, departmental or group policies, for example in terms of the legal jurisdiction in which data are held or the protection of sensitive data.
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How will you manage access and security?
', '', '
Questions to consider:
If your data is confidential (e.g. personal data not already in the public domain, confidential information or trade secrets), you should outline any appropriate security measures and note any formal standards that you will comply with e.g. ISO 27001."
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Which data are of long-term value and should be retained, shared, and/or preserved?
', '', '
Questions to consider:
Consider how the data may be reused e.g. to validate your research findings, conduct new studies, or for teaching. Decide which data to keep and for how long. This could be based on any obligations to retain certain data, the potential reuse value, what is economically viable to keep, and any additional effort required to prepare the data for data sharing and preservation. Remember to consider any additional effort required to prepare the data for sharing and preservation, such as changing file formats.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2500, 238, 1332, 646, '
What is the long-term preservation plan for the dataset?
', '', '
Questions to consider:
Consider how datasets that have long-term value will be preserved and curated beyond the lifetime of the grant. Also outline the plans for preparing and documenting data for sharing and archiving. If you do not propose to use an established repository, the data management plan should demonstrate that resources and systems will be in place to enable the data to be curated effectively beyond the lifetime of the grant.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2501, 238, 1333, 647, '
How will you share the data?
', '', '
Questions to consider:
Consider where, how, and to whom data with acknowledged long-term value should be made available. The methods used to share data will be dependent on a number of factors such as the type, size, complexity and sensitivity of data. If possible, mention earlier examples to show a track record of effective data sharing. Consider how people might acknowledge the reuse of your data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2502, 238, 1333, 648, '
Are any restrictions on data sharing required?
', '', '
Questions to consider:
Outline any expected difficulties in sharing data with acknowledged long-term value, along with causes and possible measures to overcome these. Restrictions may be due to confidentiality, lack of consent agreements or IPR, for example. Consider whether a non-disclosure agreement would give sufficient protection for confidential data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2503, 238, 1460, 649, '
Who will be responsible for data management?
', '', '
Questions to consider:
Outline the roles and responsibilities for all activities e.g. data capture, metadata production, data quality, storage and backup, data archiving and data sharing. Consider who will be responsible for ensuring relevant policies will be respected. Individuals should be named where possible.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2504, 238, 1460, 650, '
What resources will you require to deliver your plan?
', '', '
Questions to consider:
Carefully consider any resources needed to deliver the plan, e.g. software, hardware, technical expertise, etc. Where dedicated resources are needed, these should be outlined and justified.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_admin_id, NOW(), @default_admin_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3395, 101, 457, 1003, 'wergwertgreg rtghrwt
The effective date of the DMS Policy is January 25, 2023, including for:
↵The effective date of the DMS Policy is January 25, 2023, including for:
↵Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible. The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data.
The following questions are to help guide you in creating a plan, but are not specifically required.
Use this section to describe tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse.
', '', '', 0, 6, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1370, 310, 'PART IV: Additional Information', '', '', '', 0, 7, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1535, 339, 'Data Type', 'In this and all sections, URLs cannot be included in a DMS Plan.
Data type: Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1536, 339, 'Related Tools, Software and/or Code', '
In this Element and throughout the DMS Plan, URLs are not allowed.
', '', '', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1537, 339, 'Standards', '', '', '', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1538, 339, 'Data Preservation, Access, and Associated Timelines', '', '', '', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1539, 339, 'Access, Distribution, or Reuse Considerations', 'NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.
', '', '', 0, 5, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1540, 339, 'Oversight of Data Management and Sharing', '', '', '', 0, 6, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1541, 339, 'Validation schedule', '', '', '', 0, 7, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1561, 346, 'PART I: General Information (To be completed by all applicants)', '', '', '', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1562, 346, 'PART II: Data Management Sharing Plan Details', '', '', '', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1563, 346, 'PART III: Additional Information (optional)', '', '', '', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1749, 379, 'Element 1: Data Type', '
Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1750, 379, 'Element 2: Related Tools, Software and/or Code', '', '', '', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1751, 379, 'Element 3: Standards', '', '', '', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1752, 379, 'Element 4: Data preservation, Access, and Associated Timelines', 'There are various ways in which to disseminate, preserve, and make scientific data discoverable. In this section, you should describe where and when the scientific data associated with your research will be made available. The primary way to satisfy this requirement is to put your scientific data into a repository, which will support preservation of that data and provide long term access. In some cases, a repository may be specified by the funding Institute or Center; if a repository is not specified, then you have discretion in selecting the repository for your scientific data. When identifying a repository, consider how your scientific data will be made discoverable through the platform. For example, the repository’s ability to provide persistent identifiers (e.g., DOIs, handles, ARKs) for your scientific data is a good starting point to ensure consistent access. If there are restrictions as to the manner or length of time in which the scientific data can be preserved and/or accessed, be clear as to what those restrictions are in this section.
', '', '', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1753, 379, 'Element 5: Access, Distribution, or Reuse Considerations', 'NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.
', '', '', 0, 5, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1754, 379, 'Element 6: Oversight of Data Management and Sharing', '', '', '', 0, 6, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1813, 393, 'Scientific data expected to be generated and shared in the project:', '', '', '', 0, 1, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1308, 291, 'Data repositories', '', '', '', 0, 2, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1309, 291, 'Data Submission and Release Timeline', '', '', '', 0, 3, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1310, 291, 'Institutional Review Board (IRB) Review of Institutional Certification', '', '', '', 0, 4, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1311, 291, 'Appropriate Uses of the Data', '', '', '', 0, 5, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1312, 291, 'Statement of Designation of Genomic Summary Results (GSR)', '', '', '', 0, 6, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1307, 291, 'Data type', '', '', '', 0, 1, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1313, 292, 'Data sharing plan', '
Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible. The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data.
The following questions are to help guide you in creating a plan, but are not specifically required.
Use this section to describe tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse.
', '', '', 0, 6, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1370, 310, 'PART IV: Additional Information', '', '', '', 0, 7, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1535, 339, 'Data Type', 'In this and all sections, URLs cannot be included in a DMS Plan.
Data type: Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1536, 339, 'Related Tools, Software and/or Code', '
In this Element and throughout the DMS Plan, URLs are not allowed.
', '', '', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1537, 339, 'Standards', '', '', '', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1538, 339, 'Data Preservation, Access, and Associated Timelines', '', '', '', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1539, 339, 'Access, Distribution, or Reuse Considerations', 'NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.
', '', '', 0, 5, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1540, 339, 'Oversight of Data Management and Sharing', '', '', '', 0, 6, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1541, 339, 'Validation schedule', '', '', '', 0, 7, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1561, 346, 'PART I: General Information (To be completed by all applicants)', '', '', '', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1562, 346, 'PART II: Data Management Sharing Plan Details', '', '', '', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1563, 346, 'PART III: Additional Information (optional)', '', '', '', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1749, 379, 'Element 1: Data Type', '
Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1750, 379, 'Element 2: Related Tools, Software and/or Code', '', '', '', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1751, 379, 'Element 3: Standards', '', '', '', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1752, 379, 'Element 4: Data preservation, Access, and Associated Timelines', 'There are various ways in which to disseminate, preserve, and make scientific data discoverable. In this section, you should describe where and when the scientific data associated with your research will be made available. The primary way to satisfy this requirement is to put your scientific data into a repository, which will support preservation of that data and provide long term access. In some cases, a repository may be specified by the funding Institute or Center; if a repository is not specified, then you have discretion in selecting the repository for your scientific data. When identifying a repository, consider how your scientific data will be made discoverable through the platform. For example, the repository’s ability to provide persistent identifiers (e.g., DOIs, handles, ARKs) for your scientific data is a good starting point to ensure consistent access. If there are restrictions as to the manner or length of time in which the scientific data can be preserved and/or accessed, be clear as to what those restrictions are in this section.
', '', '', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1753, 379, 'Element 5: Access, Distribution, or Reuse Considerations', 'NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.
', '', '', 0, 5, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1754, 379, 'Element 6: Oversight of Data Management and Sharing', '', '', '', 0, 6, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1813, 393, 'Scientific data expected to be generated and shared in the project:', '', '', '', 0, 1, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2569, 291, 1308, '
Identify the repository or repositories where the investigator plans to submit genomic data.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data repositories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data repository in addition to an NIH-designated data repository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2574, 292, 1313, 'How do you plan to provide access to your data?', '', 'The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2579, 292, 1313, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2580, 292, 1313, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2581, 292, 1313, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.Plan Submission Date, MM/DD/YYYY
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2696, 310, 1364, 'Will data management and/or sharing activities be facilitated by individuals outside of the project team?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2695, 310, 1364, 'Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom. List the name, title, roles and responsibilities of the contact PI and any other individuals on the project team who will be responsible for oversight of data management and sharing.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2694, 310, 1364, 'Project Title
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2693, 310, 1364, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2691, 310, 1364, 'Plan Version Number. For example, 1.0.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2690, 310, 1364, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2700, 310, 1365, 'Are there any limitations or restrictions on the sharing and/or secondary use of the collected data? Restrictions may be based on informed consent under which the data were collected or specific legal, regulatory, or policy requirements.
If yes, provide justification, including a description of the data use limitations and the institutional entity or other entity that approved the limitations in the additional comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2712, 310, 1370, 'Use this section to provide additional information or context for readers and reviewers of your Data Management and Sharing Plan. Optional Additional Information:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2711, 310, 1369, 'If not yet available, provide target timelines for sharing each tool, software, and/or code developed.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2710, 310, 1369, 'List the repository or location where researchers can access the tools, software and/ or code and how they can or will be accessed. Access examples include open source and freely available, generally available for a fee in the marketplace, available only from the research team.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2709, 310, 1369, 'Briefly describe the tools, software, and/or code.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2708, 310, 1368, 'Use this section to plan for data submission to and sharing from the repositor(ies) listed in the data type section. Consider publication timelines, performance period, and data repository review and release timelines when planning data submissions and communicate through Plan updates if there are major changes to planned timelines. Shared scientific data should be made accessible as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first.
| Data Repository | Expected number and frequency of submissions | Projected timeline for first submission to repository | Projected timeline for last submission to repository | Target timelines for release | Type of persistent IDs that will be used for data releases, to enable findability and citation of shared datasets | If you will be contributing data to a dataset that is already registered with a data repository, provide that ID |
| Name the data repository described in the Data Type section. Add additional rows as necessary. | Releases associated with data underlying publications, other scheduled releases, and remaining scientific data by the end of the performance period. | Samples include dataset-level digital object identifier (DOI), accession number, globally unique identifier. |
| Data Type | Brief Description | Organism, Model, or Other Sources | Amount of Data | Standards | Shared Formats | Data Repository | Data Access Type |
| Define each data type add additional rows to describe multiple data types | Summarize how the data of this type will be managed and prepared for sharing | Projected number of participants or samples from which the data will be generated or other appropriate metrics to describe the scale of the data | List the standards that will be applied to the scientific data and associated metadata if standards exist | Formats of data to be submitted to the data repository | Name the repository where scientific data and metadata will be preserved and shared | Examples include open, registered, controlled or enclave |
If no, provide a justification and explain the factors that determine which scientific data will not be shared:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2705, 310, 1366, 'Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2704, 310, 1366, 'If yes, describe data source(s) and provide a dataset identifier (if available). For example, Digital object identifier (DOI, accession number, globally unique identifier, etc.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2703, 310, 1366, 'Will you be performing secondary analysis of extant data to generate scientific data for this project?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2702, 310, 1366, 'Describe project-associated documentation that will be made accessible to facilitate interpretation of the scientific data and where the document will be shared. Examples include study protocols and data collection instruments.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2701, 310, 1365, 'Describe what measures will be taken to protect the privacy of participants and the confidentiality of the data. Examples include de-identification, Certificates of Confidentiality, and other protective measures.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2699, 310, 1365, 'Will the individuals from whom the data are collected or derived have provided informed consent for the collection of the data?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No (Describe under what auspices data will or have been collected in the space below)", "value": "No (Describe under what auspices data will or have been collected in the space below)", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2698, 310, 1365, 'Will the project be managing and/or sharing data derived from humans?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2697, 310, 1364, 'If yes, list the individual(s) and their organization(s) and describe their role(s) and responsibilities. Examples include a data coordinating center, institutional librarians, or investigators on other NIH awards (list award numbers, if relevant).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3011, 339, 1535, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be).
', '', 'NIH Guidance
The final 2023 NIH DMS Policy (NOT-OD-21-013) defines scientific data as the recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
NIMH Guidance
Please check the 2023 NIMH DMS policy (NOT-MH-23-100) for NIMH-specific requirements in addition to the 2023 NIH DMS policy (NOT-OD-21-013).
NIMH expects data sharing plans to also include a description of the standard(s) and/or data dictionaries that will be used to describe the data set, as well as a proposed schedule to validate that the data are compliant with the data dictionary that is being used.
NIMH has certain requirements for these standards such as a set of common data elements (see NOT-MH-20-067 for non-HIV research; for HIV-related research, see NOT-MH-23-105).
The NDA provides an online Data Dictionary with a searchable interface to find data structures that awardees are expected to use for new data collection. The NDA Data Dictionary is updated as researchers extend existing data collection instruments or create new instruments. For more information, see the NDA NIMH Common Data Elements page.
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database.
', '
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
Per the Policy, even those scientific data not used to support a publication are considered to be scientific data and to fall within the final DMS Policy’s scope.
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations for NIMH
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release)
NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database. All data associated with new projects at the NIMH Repository and Genomics Resource will also be deposited in the NDA. Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP).
Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
NIMH Guidance
Investigators should review the planning section of the NIMH Data Archive website, Use of the NDA includes the NDA data harmonization approach for metadata and documentation.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3014, 339, 1536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', 'Additional Guidance from DMPTool
Tool(s) and software should be identified; then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
For human clinical and/or MRI data, please refer to the clinical imaging example on the NIMH site, also known as Sample Plan A on the NIH sharing site.
State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and describe how these data standards will be applied. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
NIMH Guidance
Applicants are strongly encouraged to use clinical and phenotypic data collection instruments/data dictionaries that have already been defined rather than create new versions of those data dictionaries. There are several required data collection instruments, mostly related to demographic and sample information, that must be used by all researchers for data harmonization purposes except for HIV-related applications (https://nda.nih.gov/contribute/harmonization-standards.html).
The NIHM Data Archive (NDA) provides its own standards for metadata and data structures. The standards that a PI intends to use for compatibility with the NDA should be briefly described in this section.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data.
Furthermore, if formal standards such as specific imaging or sequencing filetypes, descriptive metadata, collection formats, etc., beyond the NDA standards will be used, that should also be addressed in this Element.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)
', '', 'NIH Guidance
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016. Selecting a Data Repository Page of the NIH sharing website.
NIMH Guidance
Research funded by the NIMH are required to deposit all raw and analyzed data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) from studies involving human subjects into the NIMH Data Archive (NDA).
NIMH Guidance on NIH GDS Policy Considerations
NOT-MH-23-100 requires that the NIMH Data Archive (NDA) serve as the repository for genomic data funded by the NIMH unless the NIMH approves a different data repository during the negotiation of the terms and conditions of the award.
Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP Submission Process). After registration, all data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) will be deposited in the NDA. A link to NDA will be added to the dbGaP registration. Aggregating the genomic data in a single cloud-based data archive will facilitate the re-analysis, replication, and additional analyses of these important data sets. Computational credits may be available to conduct these analyses in the cloud.
All data associated with new projects at the NIMH Repository and Genomics Resource will be deposited in the NDA. Appropriate data will then be transmitted to the NIMH Repository and Genomics Resource for quality control and to allow the research community to identify samples that are relevant to their research efforts.
Additional Guidance from DMPTool
The NIMH notice of data sharing policy does not provide specific guidance on access and preservation of non-human data for the data management and sharing policy. Consult the NIMH data sharing website or the trans-NIH repositories list for further possibilities.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
Additional Guidance from DMPTool
NIMH Data Archive data collections have DOIs to help make the data in them findable and identifiable.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3018, 339, 1538, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. The NIMH further specifies that data must be shared with the research community when papers using the data have been accepted for publication or at the end of the award period (including the first no cost extension). Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
NIH GDS Policy Considerations
Genomic data is subject to further guidance on release expectations and timelines.
NIMH Guidance
The general expectation is that data from NIMH-funded awards that involve human subjects will be submitted to NDA every 6 months throughout the duration of the award (typically January and July). Awardees will provide a Data Submission Agreement signed by the principal investigator and an institutional business official within 6 months of the notice of award. Although submission does not lead to release of the data, awardees are encouraged to share basic demographic and raw baseline data shortly after data submission to encourage collaborations in the research community.
In addition to regular submission of data associated with an award, awardees are expected to separately submit to NDA the specific data that was used for each resulting publication by creating an NDA Study.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3019, 339, 1539, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.
', '', 'NIH Guidance
The DMS Policy acknowledges certain factors (i.e., legal, ethical, or technical) that may affect the extent to which scientific data are preserved and shared.
In addition, NOT-OD-22-213 addresses specific considerations about human subjects privacy.
Additional Guidance from DMPTool
This is the section to describe what legal, ethical, or technical issues may require limiting the sharing of your data. Examples may include ethical considerations such as IACUC restrictions on sharing videos or images of procedures. Other nonhuman data factors affecting distribution may include existing legal limits such as data licenses or use agreements or technical limits about the size or structure of the data.
For human data, the NIMH requires the application of privacy protections through the use of the NDA. It is likely to be sufficient in this subsection to say that human ethics require the use of the NIMH Data Archive for privacy.
NIH GDS Policy Considerations
Genomic data may have further considerations to address. The NIH now expects a single data sharing plan at the time of funding application to satisfy both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198). How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', '
The NDA uses controlled access. Summary information on the data shared in NDA will be available in the NDA Query Tool without the need for an NDA user account. To request access to record-level human subject data, researchers must submit a Data Access Request.
Additional guidance from DMPTool
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3021, 339, 1539, '
Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
NIH Guidance
Effective data stewardship and protection of human research participant (hereinafter “participant”) privacy are achieved in tandem through responsible scientific data sharing practices. Accordingly, NIH has developed supplemental information to the DMS Policy to assist researchers in responsible data sharing by establishing 1) operational principles for protecting participants’ privacy when sharing scientific data, 2) best practices for implementing these principles, and 3) points to consider for choosing whether to designate scientific data for controlled access.
NIMH Guidance
Applicants should also plan to collect the data needed to generate global unique identifiers (GUIDs) for each study subject. The GUID, or Global Unique Identifier, is used as an identifier for a research participant. The GUID provides a secure mechanism to link research participants within and across research project datasets in NDA.
Informed consent documents should describe how study data will be shared with NDA and the research community. The NDA has provided a plain-language description of the NDA as an example when creating informed consent language.
NIMH also expects these additional points to be considered in human subjects research.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3022, 339, 1540, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
NIH Guidance
This element refers to oversight by the funded institution, rather than by NIH. The DMS Policy does not create any expectations about who will be responsible for Plan oversight at the institution.
Additional guidance from DMPTool
Please confer with your Office of Sponsored Programs, Office of Research, etc., about any additional oversight considerations. Oversight of human data with the NIMH Data Archive may have specific factors to address. All NIMH applicants should consult local campus departments and policies about oversight.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
The Data Management and Sharing Plan must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used.
', '', 'NIMH Guidance
All NIMH DMS Plans must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used. In cases where a data dictionary has been defined in the NIMH Data Archive, the NDA Data Validation and Uploading Tool should be used to ensure your data files are harmonized to the NDA Data Dictionary. Compliance with the approved data management and sharing plan will become a term and condition in the Notice of Award and will be monitored by the NIMH throughout the duration of the award.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3065, 346, 1562, '
Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3072, 346, 1562, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3071, 346, 1562, 'Element 4: Data Preservation, Access, and Timelines
Explain if data sharing timelines will not meet expectations of the DMS or other policies, if applicable.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3070, 346, 1562, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3069, 346, 1562, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3068, 346, 1562, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3067, 346, 1562, 'Element 1: Data Type
Describe DMS Plan Elements 1-6 in the section below with free text. To maximize the use of structured information in writing a Plan (e.g., data types, repositories) with a drop-down menu option, please proceed to the adjacent tab labeled “Research Outputs."
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3066, 346, 1562, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3064, 346, 1562, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3063, 346, 1562, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3062, 346, 1561, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3061, 346, 1561, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3060, 346, 1561, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3059, 346, 1561, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3058, 346, 1561, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3073, 346, 1562, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3081, 346, 1563, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3080, 346, 1563, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3079, 346, 1563, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3078, 346, 1562, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3076, 346, 1562, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3075, 346, 1562, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3074, 346, 1562, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3077, 346, 1562, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3533, 379, 1749, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
', '', 'NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Polcies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3534, 379, 1749, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3537, 379, 1751, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3544, 379, 1754, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3543, 379, 1753, '5C. Protections for privacy, rights, and confidentiality of human research participants: if generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3542, 379, 1753, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3541, 379, 1753, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing.
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3540, 379, 1752, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3539, 379, 1752, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3538, 379, 1752, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3536, 379, 1750, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3535, 379, 1749, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3685, 393, 1813, 'Add one row for each broad type of data to be generated and shared in the project. If data to be generated is not yet known or otherwise does not conform to the columns in this table, explain in the text box below. Be sure to describe any data that will be generated but not shared in Section II and provide a strong justification for why the data cannot be shared. Complete Section VII if generating any genomic data that is subject to the NIH Genomic Data Sharing (GDS) policy.
', '', 'If data to be generated is not yet known or otherwise does not conform to the columns in this table, delete the table and write in an explanation of extenuating circumstances instead.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2569, 291, 1308, 'Identify the repository or repositories where the investigator plans to submit genomic data.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data repositories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data repository in addition to an NIH-designated data repository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2574, 292, 1313, 'How do you plan to provide access to your data?', '', 'The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2579, 292, 1313, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2580, 292, 1313, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2581, 292, 1313, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.Plan Submission Date, MM/DD/YYYY
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2696, 310, 1364, 'Will data management and/or sharing activities be facilitated by individuals outside of the project team?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2695, 310, 1364, 'Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom. List the name, title, roles and responsibilities of the contact PI and any other individuals on the project team who will be responsible for oversight of data management and sharing.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2694, 310, 1364, 'Project Title
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2693, 310, 1364, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2691, 310, 1364, 'Plan Version Number. For example, 1.0.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2690, 310, 1364, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2700, 310, 1365, 'Are there any limitations or restrictions on the sharing and/or secondary use of the collected data? Restrictions may be based on informed consent under which the data were collected or specific legal, regulatory, or policy requirements.
If yes, provide justification, including a description of the data use limitations and the institutional entity or other entity that approved the limitations in the additional comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2712, 310, 1370, 'Use this section to provide additional information or context for readers and reviewers of your Data Management and Sharing Plan. Optional Additional Information:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2711, 310, 1369, 'If not yet available, provide target timelines for sharing each tool, software, and/or code developed.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2710, 310, 1369, 'List the repository or location where researchers can access the tools, software and/ or code and how they can or will be accessed. Access examples include open source and freely available, generally available for a fee in the marketplace, available only from the research team.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2709, 310, 1369, 'Briefly describe the tools, software, and/or code.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2708, 310, 1368, 'Use this section to plan for data submission to and sharing from the repositor(ies) listed in the data type section. Consider publication timelines, performance period, and data repository review and release timelines when planning data submissions and communicate through Plan updates if there are major changes to planned timelines. Shared scientific data should be made accessible as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first.
| Data Repository | Expected number and frequency of submissions | Projected timeline for first submission to repository | Projected timeline for last submission to repository | Target timelines for release | Type of persistent IDs that will be used for data releases, to enable findability and citation of shared datasets | If you will be contributing data to a dataset that is already registered with a data repository, provide that ID |
| Name the data repository described in the Data Type section. Add additional rows as necessary. | Releases associated with data underlying publications, other scheduled releases, and remaining scientific data by the end of the performance period. | Samples include dataset-level digital object identifier (DOI), accession number, globally unique identifier. |
| Data Type | Brief Description | Organism, Model, or Other Sources | Amount of Data | Standards | Shared Formats | Data Repository | Data Access Type |
| Define each data type add additional rows to describe multiple data types | Summarize how the data of this type will be managed and prepared for sharing | Projected number of participants or samples from which the data will be generated or other appropriate metrics to describe the scale of the data | List the standards that will be applied to the scientific data and associated metadata if standards exist | Formats of data to be submitted to the data repository | Name the repository where scientific data and metadata will be preserved and shared | Examples include open, registered, controlled or enclave |
If no, provide a justification and explain the factors that determine which scientific data will not be shared:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2705, 310, 1366, 'Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2704, 310, 1366, 'If yes, describe data source(s) and provide a dataset identifier (if available). For example, Digital object identifier (DOI, accession number, globally unique identifier, etc.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2703, 310, 1366, 'Will you be performing secondary analysis of extant data to generate scientific data for this project?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2702, 310, 1366, 'Describe project-associated documentation that will be made accessible to facilitate interpretation of the scientific data and where the document will be shared. Examples include study protocols and data collection instruments.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2701, 310, 1365, 'Describe what measures will be taken to protect the privacy of participants and the confidentiality of the data. Examples include de-identification, Certificates of Confidentiality, and other protective measures.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2699, 310, 1365, 'Will the individuals from whom the data are collected or derived have provided informed consent for the collection of the data?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No (Describe under what auspices data will or have been collected in the space below)", "value": "No (Describe under what auspices data will or have been collected in the space below)", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2698, 310, 1365, 'Will the project be managing and/or sharing data derived from humans?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2697, 310, 1364, 'If yes, list the individual(s) and their organization(s) and describe their role(s) and responsibilities. Examples include a data coordinating center, institutional librarians, or investigators on other NIH awards (list award numbers, if relevant).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3011, 339, 1535, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be).
', '', 'NIH Guidance
The final 2023 NIH DMS Policy (NOT-OD-21-013) defines scientific data as the recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
NIMH Guidance
Please check the 2023 NIMH DMS policy (NOT-MH-23-100) for NIMH-specific requirements in addition to the 2023 NIH DMS policy (NOT-OD-21-013).
NIMH expects data sharing plans to also include a description of the standard(s) and/or data dictionaries that will be used to describe the data set, as well as a proposed schedule to validate that the data are compliant with the data dictionary that is being used.
NIMH has certain requirements for these standards such as a set of common data elements (see NOT-MH-20-067 for non-HIV research; for HIV-related research, see NOT-MH-23-105).
The NDA provides an online Data Dictionary with a searchable interface to find data structures that awardees are expected to use for new data collection. The NDA Data Dictionary is updated as researchers extend existing data collection instruments or create new instruments. For more information, see the NDA NIMH Common Data Elements page.
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database.
', '
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
Per the Policy, even those scientific data not used to support a publication are considered to be scientific data and to fall within the final DMS Policy’s scope.
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations for NIMH
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release)
NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database. All data associated with new projects at the NIMH Repository and Genomics Resource will also be deposited in the NDA. Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP).
Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
NIMH Guidance
Investigators should review the planning section of the NIMH Data Archive website, Use of the NDA includes the NDA data harmonization approach for metadata and documentation.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3014, 339, 1536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', 'Additional Guidance from DMPTool
Tool(s) and software should be identified; then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
For human clinical and/or MRI data, please refer to the clinical imaging example on the NIMH site, also known as Sample Plan A on the NIH sharing site.
State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and describe how these data standards will be applied. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
NIMH Guidance
Applicants are strongly encouraged to use clinical and phenotypic data collection instruments/data dictionaries that have already been defined rather than create new versions of those data dictionaries. There are several required data collection instruments, mostly related to demographic and sample information, that must be used by all researchers for data harmonization purposes except for HIV-related applications (https://nda.nih.gov/contribute/harmonization-standards.html).
The NIHM Data Archive (NDA) provides its own standards for metadata and data structures. The standards that a PI intends to use for compatibility with the NDA should be briefly described in this section.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data.
Furthermore, if formal standards such as specific imaging or sequencing filetypes, descriptive metadata, collection formats, etc., beyond the NDA standards will be used, that should also be addressed in this Element.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)
', '', 'NIH Guidance
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016. Selecting a Data Repository Page of the NIH sharing website.
NIMH Guidance
Research funded by the NIMH are required to deposit all raw and analyzed data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) from studies involving human subjects into the NIMH Data Archive (NDA).
NIMH Guidance on NIH GDS Policy Considerations
NOT-MH-23-100 requires that the NIMH Data Archive (NDA) serve as the repository for genomic data funded by the NIMH unless the NIMH approves a different data repository during the negotiation of the terms and conditions of the award.
Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP Submission Process). After registration, all data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) will be deposited in the NDA. A link to NDA will be added to the dbGaP registration. Aggregating the genomic data in a single cloud-based data archive will facilitate the re-analysis, replication, and additional analyses of these important data sets. Computational credits may be available to conduct these analyses in the cloud.
All data associated with new projects at the NIMH Repository and Genomics Resource will be deposited in the NDA. Appropriate data will then be transmitted to the NIMH Repository and Genomics Resource for quality control and to allow the research community to identify samples that are relevant to their research efforts.
Additional Guidance from DMPTool
The NIMH notice of data sharing policy does not provide specific guidance on access and preservation of non-human data for the data management and sharing policy. Consult the NIMH data sharing website or the trans-NIH repositories list for further possibilities.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
Additional Guidance from DMPTool
NIMH Data Archive data collections have DOIs to help make the data in them findable and identifiable.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3018, 339, 1538, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. The NIMH further specifies that data must be shared with the research community when papers using the data have been accepted for publication or at the end of the award period (including the first no cost extension). Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
NIH GDS Policy Considerations
Genomic data is subject to further guidance on release expectations and timelines.
NIMH Guidance
The general expectation is that data from NIMH-funded awards that involve human subjects will be submitted to NDA every 6 months throughout the duration of the award (typically January and July). Awardees will provide a Data Submission Agreement signed by the principal investigator and an institutional business official within 6 months of the notice of award. Although submission does not lead to release of the data, awardees are encouraged to share basic demographic and raw baseline data shortly after data submission to encourage collaborations in the research community.
In addition to regular submission of data associated with an award, awardees are expected to separately submit to NDA the specific data that was used for each resulting publication by creating an NDA Study.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3019, 339, 1539, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.
', '', 'NIH Guidance
The DMS Policy acknowledges certain factors (i.e., legal, ethical, or technical) that may affect the extent to which scientific data are preserved and shared.
In addition, NOT-OD-22-213 addresses specific considerations about human subjects privacy.
Additional Guidance from DMPTool
This is the section to describe what legal, ethical, or technical issues may require limiting the sharing of your data. Examples may include ethical considerations such as IACUC restrictions on sharing videos or images of procedures. Other nonhuman data factors affecting distribution may include existing legal limits such as data licenses or use agreements or technical limits about the size or structure of the data.
For human data, the NIMH requires the application of privacy protections through the use of the NDA. It is likely to be sufficient in this subsection to say that human ethics require the use of the NIMH Data Archive for privacy.
NIH GDS Policy Considerations
Genomic data may have further considerations to address. The NIH now expects a single data sharing plan at the time of funding application to satisfy both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198). How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', '
The NDA uses controlled access. Summary information on the data shared in NDA will be available in the NDA Query Tool without the need for an NDA user account. To request access to record-level human subject data, researchers must submit a Data Access Request.
Additional guidance from DMPTool
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3021, 339, 1539, '
Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
NIH Guidance
Effective data stewardship and protection of human research participant (hereinafter “participant”) privacy are achieved in tandem through responsible scientific data sharing practices. Accordingly, NIH has developed supplemental information to the DMS Policy to assist researchers in responsible data sharing by establishing 1) operational principles for protecting participants’ privacy when sharing scientific data, 2) best practices for implementing these principles, and 3) points to consider for choosing whether to designate scientific data for controlled access.
NIMH Guidance
Applicants should also plan to collect the data needed to generate global unique identifiers (GUIDs) for each study subject. The GUID, or Global Unique Identifier, is used as an identifier for a research participant. The GUID provides a secure mechanism to link research participants within and across research project datasets in NDA.
Informed consent documents should describe how study data will be shared with NDA and the research community. The NDA has provided a plain-language description of the NDA as an example when creating informed consent language.
NIMH also expects these additional points to be considered in human subjects research.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3022, 339, 1540, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
NIH Guidance
This element refers to oversight by the funded institution, rather than by NIH. The DMS Policy does not create any expectations about who will be responsible for Plan oversight at the institution.
Additional guidance from DMPTool
Please confer with your Office of Sponsored Programs, Office of Research, etc., about any additional oversight considerations. Oversight of human data with the NIMH Data Archive may have specific factors to address. All NIMH applicants should consult local campus departments and policies about oversight.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
The Data Management and Sharing Plan must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used.
', '', 'NIMH Guidance
All NIMH DMS Plans must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used. In cases where a data dictionary has been defined in the NIMH Data Archive, the NDA Data Validation and Uploading Tool should be used to ensure your data files are harmonized to the NDA Data Dictionary. Compliance with the approved data management and sharing plan will become a term and condition in the Notice of Award and will be monitored by the NIMH throughout the duration of the award.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3065, 346, 1562, '
Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3072, 346, 1562, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3071, 346, 1562, 'Element 4: Data Preservation, Access, and Timelines
Explain if data sharing timelines will not meet expectations of the DMS or other policies, if applicable.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3070, 346, 1562, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3069, 346, 1562, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3068, 346, 1562, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3067, 346, 1562, 'Element 1: Data Type
Describe DMS Plan Elements 1-6 in the section below with free text. To maximize the use of structured information in writing a Plan (e.g., data types, repositories) with a drop-down menu option, please proceed to the adjacent tab labeled “Research Outputs."
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3066, 346, 1562, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3064, 346, 1562, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3063, 346, 1562, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3062, 346, 1561, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3061, 346, 1561, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3060, 346, 1561, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3059, 346, 1561, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3058, 346, 1561, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3073, 346, 1562, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3081, 346, 1563, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3080, 346, 1563, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3079, 346, 1563, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3078, 346, 1562, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3076, 346, 1562, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3075, 346, 1562, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3074, 346, 1562, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3077, 346, 1562, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3533, 379, 1749, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
', '', 'NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Polcies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3534, 379, 1749, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3537, 379, 1751, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3544, 379, 1754, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3543, 379, 1753, '5C. Protections for privacy, rights, and confidentiality of human research participants: if generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3542, 379, 1753, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3541, 379, 1753, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing.
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3540, 379, 1752, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3539, 379, 1752, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3538, 379, 1752, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3536, 379, 1750, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3535, 379, 1749, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3685, 393, 1813, 'Add one row for each broad type of data to be generated and shared in the project. If data to be generated is not yet known or otherwise does not conform to the columns in this table, explain in the text box below. Be sure to describe any data that will be generated but not shared in Section II and provide a strong justification for why the data cannot be shared. Complete Section VII if generating any genomic data that is subject to the NIH Genomic Data Sharing (GDS) policy.
', '', 'If data to be generated is not yet known or otherwise does not conform to the columns in this table, delete the table and write in an explanation of extenuating circumstances instead.
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↵The effective date of the DMS Policy is January 25, 2023, including for:
↵The effective date of the DMS Policy is January 25, 2023, including for:
↵The effective date of the DMS Policy is January 25, 2023, including for:
↵The effective date of the DMS Policy is January 25, 2023, including for:
↵The effective date of the DMS Policy is January 25, 2023, including for:
↵The effective date of the DMS Policy is January 25, 2023, including for:
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↵Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible. The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider these questions below:
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The following questions are to help guide you in creating a plan, but are not specifically required.
Use this section to describe tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse.
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Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible. The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider these questions below:
', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (3247, 519, 1313, 'Data sharing plan', 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible. The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider these questions below:
', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (3335, 529, 1313, 'Data sharing plan', 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible. The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data.
The following questions are to help guide you in creating a plan, but are not specifically required.
Use this section to describe tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse.
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Data type: Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5402, 836, 1536, 'Related Tools, Software and/or Code', '
In this Element and throughout the DMS Plan, URLs are not allowed.
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', '', '', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5406, 836, 1540, 'Oversight of Data Management and Sharing', '', '', '', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5407, 836, 1541, 'Validation schedule', '', '', '', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5437, 845, 1561, 'PART I: General Information (To be completed by all applicants)', '', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5438, 845, 1562, 'PART II: Data Management Sharing Plan Details', '', '', '', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5439, 845, 1563, 'PART III: Additional Information (optional)', '', '', '', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6098, 935, 1749, 'Element 1: Data Type', '
Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6099, 935, 1750, 'Element 2: Related Tools, Software and/or Code', '', '', '', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6100, 935, 1751, 'Element 3: Standards', '', '', '', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6101, 935, 1752, 'Element 4: Data preservation, Access, and Associated Timelines', 'There are various ways in which to disseminate, preserve, and make scientific data discoverable. In this section, you should describe where and when the scientific data associated with your research will be made available. The primary way to satisfy this requirement is to put your scientific data into a repository, which will support preservation of that data and provide long term access. In some cases, a repository may be specified by the funding Institute or Center; if a repository is not specified, then you have discretion in selecting the repository for your scientific data. When identifying a repository, consider how your scientific data will be made discoverable through the platform. For example, the repository’s ability to provide persistent identifiers (e.g., DOIs, handles, ARKs) for your scientific data is a good starting point to ensure consistent access. If there are restrictions as to the manner or length of time in which the scientific data can be preserved and/or accessed, be clear as to what those restrictions are in this section.
', '', '', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6102, 935, 1753, 'Element 5: Access, Distribution, or Reuse Considerations', 'NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.
', '', '', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6103, 935, 1754, 'Element 6: Oversight of Data Management and Sharing', '', '', '', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6104, 936, 1749, 'Element 1: Data Type', '
Briefly describe the scientific data to be managed, preserved, and shared.
', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6105, 936, 1750, 'Element 2: Related Tools, Software and/or Code', '', '', '', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6106, 936, 1751, 'Element 3: Standards', '', '', '', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6107, 936, 1752, 'Element 4: Data preservation, Access, and Associated Timelines', 'There are various ways in which to disseminate, preserve, and make scientific data discoverable. In this section, you should describe where and when the scientific data associated with your research will be made available. The primary way to satisfy this requirement is to put your scientific data into a repository, which will support preservation of that data and provide long term access. In some cases, a repository may be specified by the funding Institute or Center; if a repository is not specified, then you have discretion in selecting the repository for your scientific data. When identifying a repository, consider how your scientific data will be made discoverable through the platform. For example, the repository’s ability to provide persistent identifiers (e.g., DOIs, handles, ARKs) for your scientific data is a good starting point to ensure consistent access. If there are restrictions as to the manner or length of time in which the scientific data can be preserved and/or accessed, be clear as to what those restrictions are in this section.
', '', '', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6108, 936, 1753, 'Element 5: Access, Distribution, or Reuse Considerations', 'NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.
', '', '', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6109, 936, 1754, 'Element 6: Oversight of Data Management and Sharing', '', '', '', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6198, 945, 1749, 'Element 1: Data Type', '
Briefly describe the scientific data to be managed, preserved, and shared.
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', '', '', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6203, 945, 1754, 'Element 6: Oversight of Data Management and Sharing', '', '', '', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (6355, 967, 1813, 'Scientific data expected to be generated and shared in the project:', '', '', '', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (85, 16, 85, 2574, '
Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'Help with a data sharing plan:
The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
Explain whether the research being considered for funding involves human data, non-human data, or both.
', '', 'Information to be included in this section:
Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
', '', 'For human genomic data, investigators are expected to register all studies in the database of Genotypes and Phenotypes (dbGaP) by the time data cleaning and quality control measures begin in addition to submitting the data to the relevant NIH-designated data repository (e.g., dbGaP, Gene Expression Omnibus (GEO), Sequence Read Archive (SRA), the Cancer Genomics Hub) after registration.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
Data in unrestricted-access repositories (e.g., The 1000 Genomes Project) are publicly available to anyone. Controlled-access data (e.g., data in dbGaP) are made available for secondary research only after investigators have obtained appropriate approval to use the requested data for their proposed project.
Provide a timeline for sharing data in a timely manner.
', '', 'In general, NIH will release human genomic data no later than six months after the data have been submitted to NIH-designated data repositories and cleaned, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination of research findings. Investigators should make non-human genomic data publicly available no later than the date of initial publication. However, availability before publication may be expected for certain data, projects (e.g., data from projects with broad utility as a resource for the scientific community such as microbial population-based genomic studies), or by the funding NIH IC.
Note: The Supplemental Information to the GDS Policy provides expectations for the timelines of data submission and release based on the level of data processing, and additional information about the data levels.
State whether an Institutional Review Board (IRB) or analogous review body has reviewed the genomic data sharing aspects of your project, or provide a timeline for such review.
', '', 'IRB review of the investigator’s proposal for data submission is an element of the Institutional Certification which assures that the proposal for data submission and sharing is appropriate. Please keep in mind that an Institutional Certification is generally required for extramural investigators prior to NIH grant award along with other Just- in-Time information or finalization of a contract. For NIH intramural investigators, an Institutional Certification memorandum should be completed and sent from the SD, or delegate, to the IC Genomic Program Administrator (GPA) before research is begun, whenever possible.
Points to Consider for Institutions and Institutional Review Boards in Developing Institutional Certifications for Submitting Human Data under the Genomic Data Sharing Policy.
Describe the appropriate use of the data.
', '', 'NIH-GDS: Appropriate uses of the data:
Under the GDS Policy, data is expected to be shared for broad research purposes. If such use of the data is not appropriate, as expressed in informed consent documents of the research participants whose data are included in the dataset, any limitations on the data use should be described in the Institutional Certification. NIH provides standard language (see Links tab for URL) to guide the development of data use limitations.
Explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing .
', '', 'NIH-GDS: Request for an exception to submission:
If submission of human data generated in the study would not be appropriate because the Institutional Certification (see Links tab for URL) criteria cannot be met, the investigator should explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing. If the funding IC grants an exception to submission, the research will be registered in dbGaP and the reason for the exception and the alternative sharing plan will be described. For NIH intramural studies, the NIH Deputy Director for Intramural Research will make the final decision on the exception request, after the IC has made its determination.
The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
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Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Database of Genotypes and Phenotypes (dbGaP)
NCBI GEO Gene Expressioin Omnibus.https://www.ncbi.nlm.nih.gov/geo/
NCBI SRA Sequence Read Archive. https://www.ncbi.nlm.nih.gov/sra
NIH National Cancer Institute. Genomic Data Commons. https://gdc.cancer.gov/
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Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1248, 180, 860, 2573, 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
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Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'Proposed Text:
"Grantees should note that, under the NIH Grants Policy Statement, they are required to keep the data for 3 years following closeout of a grant or contract agreement. NIH expects the timely release and sharing of data to be no later than the acceptance for publication of the main findings from the final dataset.
It is the responsibility of the investigators, their Institutional Review Board (IRB), and their institution to protect the rights of subjects and the confidentiality of the data. Prior to sharing, data should be redacted to strip all identifiers, and effective strategies should be adopted to minimize risks of unauthorized disclosure of personal identifiers. Researchers who are planning clinical trials and intend to share the resulting data should think carefully about the study design, the informed consent documents, and the structure of the resulting dataset prior to the initiation of the study. Investigators who are working for or who are themselves covered entities under the Health Insurance Portability and Accountability Act (HIPAA) must consider issues related to the Privacy Rule. See linked guidance for more information regarding proprietary data.
Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based" (NIH Data Sharing Policy and Implementation Guidance)."
Original Text:
Help with a data sharing plan:
The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
NIH Data Standards and Common Data Elements Resource Guide (.doc)
NIH Common Data Element (CDE) Resource Portal. https://www.nlm.nih.gov/cde/
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', '', 'The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
NIH Data Standards and Common Data Elements Resource Guide (.doc)
NIH Common Data Element (CDE) Resource Portal. https://www.nlm.nih.gov/cde/
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2451, 253, 1426, 2568, 'The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
', '', 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
', '', 'Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
', '', 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
', '', 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
', '', 'Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
', '', 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
Selecting a Data Repository
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThe method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5613, 506, 3195, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.Selecting a Data Repository
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5716, 517, 3245, 2579, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5717, 517, 3245, 2580, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5718, 517, 3245, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
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There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
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There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5902, 529, 3335, 2579, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5903, 529, 3335, 2580, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5904, 529, 3335, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
', '', 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
', '', 'Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
', '', 'NIH encourages patenting of technology suitable for subsequent private investment that may lead to the development of products that address public needs without impeding research. However, it is important to note that naturally occurring DNA sequences are not patentable in the U.S. Therefore, basic sequence data and certain related information (e.g. genotypes, haplotypes, p-values, allele frequencies) are pre-competitive. Such data made available through NIH-designated data repositories, and all conclusions derived directly from them, should remain freely available, without any licensing requirements.
NIH encourages broad use of NIH-funded genomic data that is consistent with a responsible approach to management of intellectual property derived from downstream discoveries, as outlined in the NIH Best Practices for the Licensing of Genomic Inventions and Section 8.2.3. Sharing Research Resources, of the NIH Grants Policy Statement. NIH discourages the use of patents to prevent the use of or to block access to genomic or genotype-phenotype data developed with NIH support.
', '', 'The file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6964, 600, 3873, 3537, 'An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6965, 600, 3874, 3538, 'The name of the repository(ies) where scientific data and metadata arising from the project will be archived.', '', 'NIH GuidanceSelecting a Data Repository
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6966, 600, 3874, 3539, 'How the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', '', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6967, 600, 3874, 3540, 'When the scientific data will be made available to other users (i.e., the larger research community, institutions, and/or the broader public) and for how long.', '', 'NIH GuidanceData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6968, 600, 3875, 3541, 'Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
', 'For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6970, 600, 3876, 3544, 'Indicate how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom (e.g., titles, roles).', '', 'NIH Guidance
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
Additional Guidance
List the roles responsible for data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Include the name (if available), title, affiliation, and ORCIDs where possible.
If this is a collaborative project across institutions, explain how data management tasks will be addressed across partners.
Identify which individual (or role) will be responsible for implementing, updating, and revising the DMSP.
Explain how the necessary resources (for example personnel time) to prepare the data for sharing/preservation have been budgeted. Consider and justify any resources needed to adhere to the DMP. These may include curating data and developing documentation, infrastructure necessary to provide local management and preservation, and data deposit fees.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7198, 611, 3972, 3533, 'A general summary of the types and estimated amount of scientific data to be generated and/or used in the research. Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be)', '', 'NIH GuidanceThe file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7202, 611, 3974, 3537, 'An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7203, 611, 3975, 3538, 'The name of the repository(ies) where scientific data and metadata arising from the project will be archived.', '', 'NIH GuidanceSelecting a Data Repository
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7204, 611, 3975, 3539, 'How the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', '', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7205, 611, 3975, 3540, 'When the scientific data will be made available to other users (i.e., the larger research community, institutions, and/or the broader public) and for how long.', '', 'NIH GuidanceData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7206, 611, 3976, 3541, 'Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
', 'For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
For researchers selecting controlled access repositories
Given the sensitive nature of the dataset, de-identified human subjects data will be made available in ________ data repository, which restricts access to the data to qualified investigators with an appropriate research question who sign a data use agreement. [Describe data repository access methods and security measures].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7208, 611, 3977, 3544, 'Indicate how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom (e.g., titles, roles).', '', '
NIH Guidance
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
Additional Guidance
List the roles responsible for data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Include the name (if available), title, affiliation, and ORCIDs where possible.
If this is a collaborative project across institutions, explain how data management tasks will be addressed across partners.
Identify which individual (or role) will be responsible for implementing, updating, and revising the DMSP.
Explain how the necessary resources (for example personnel time) to prepare the data for sharing/preservation have been budgeted. Consider and justify any resources needed to adhere to the DMP. These may include curating data and developing documentation, infrastructure necessary to provide local management and preservation, and data deposit fees.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8616, 693, 4394, 2568, 'Identify the repository or repositories where the investigator plans to submit genomic data.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data repositories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data repository in addition to an NIH-designated data repository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8620, 693, 4398, 2572, 'Describe any limitations on the use of the data. These limitations should be decided by the submitting investigator and their institution, in consultation with the IRB or equivalent body. They should be based on the language in the informed consent form or the recommendations of an IRB or equivalent body.The file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8639, 696, 4408, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceSelecting a Data Repository
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8640, 696, 4408, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', '', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8641, 696, 4408, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long dataData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8642, 696, 4409, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'Additional GuidanceCertain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
Issues to consider:
For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
For researchers selecting controlled access repositories
Given the sensitive nature of the dataset, de-identified human subjects data will be made available in ________ data repository, which restricts access to the data to qualified investigators with an appropriate research question who sign a data use agreement. [Describe data repository access methods and security measures].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8644, 696, 4410, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by
NIH Guidance
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
Additional Guidance
List the roles responsible for data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Include the name (if available), title, affiliation, and ORCIDs where possible.
If this is a collaborative project across institutions, explain how data management tasks will be addressed across partners.
Identify which individual (or role) will be responsible for implementing, updating, and revising the DMSP.
Explain how the necessary resources (for example personnel time) to prepare the data for sharing/preservation have been budgeted. Consider and justify any resources needed to adhere to the DMP. These may include curating data and developing documentation, infrastructure necessary to provide local management and preservation, and data deposit fees.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8645, 696, 4409, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8646, 698, 4411, 2568, 'Identify the repository or repositories where the investigator plans to submit genomic data.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data repositories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data repository in addition to an NIH-designated data repository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8650, 698, 4415, 2572, 'Describe any limitations on the use of the data. These limitations should be decided by the submitting investigator and their institution, in consultation with the IRB or equivalent body. They should be based on the language in the informed consent form or the recommendations of an IRB or equivalent body.The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data.
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
', 'To facilitate interpretation of the data, ______ [e.g., metadata, documentation, protocols, data collection instruments] will be shared and associated with the relevant datasets.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8670, 704, 4429, 3536, '
State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified; plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8671, 704, 4430, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8672, 704, 4431, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceGenomic data has further guidance and considerations to address in the Plan.
Additional Guidance
See NOT-OD-21-016 and other guidance on selecting a repository, for details on repository considerations. In brief, the first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8673, 704, 4431, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8674, 704, 4431, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8675, 704, 4432, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data-sharing plan at the time of funding application to satisfy both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional GuidanceSome data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8676, 704, 4432, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8677, 704, 4432, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
Issues to consider:
For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
For researchers selecting controlled access repositories
Given the sensitive nature of the dataset, de-identified human subjects data will be made available in ________ data repository, which restricts access to the data to qualified investigators with an appropriate research question who sign a data use agreement. [Describe data repository access methods and security measures].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8678, 704, 4433, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', '
Additional Guidance:
Describe how and by whom compliance with this Plan will be managed. If roles will include the addition of study personnel for data management oversight, see NIH’s supplementary guidance on allowable costs for data management and sharing. Budget considerations are not addressed in this section but instead, you will request funds towards DMS costs as a line item in the budget form, and provide a brief summary of the DMS Plan and a description of the requested DMS costs in the budget justification.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8718, 708, 4443, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8719, 708, 4443, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8720, 708, 4443, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8721, 708, 4444, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8722, 708, 4445, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8723, 708, 4446, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceNIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Genomic data has further guidance and considerations to address in the Plan.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8724, 708, 4446, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8725, 708, 4446, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8726, 708, 4447, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8727, 708, 4447, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8728, 708, 4447, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8729, 708, 4448, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Additional DMPTool Guidance:
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8730, 709, 4449, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8731, 709, 4449, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8732, 709, 4449, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8733, 709, 4450, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8734, 709, 4451, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8735, 709, 4452, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceNIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Genomic data has further guidance and considerations to address in the Plan.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8736, 709, 4452, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8737, 709, 4452, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8738, 709, 4453, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8739, 709, 4453, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8740, 709, 4453, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8741, 709, 4454, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8768, 713, 4467, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8769, 713, 4467, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8770, 713, 4467, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8771, 713, 4468, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8772, 713, 4469, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8773, 713, 4470, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceNIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8774, 713, 4470, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8775, 713, 4470, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8776, 713, 4471, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8777, 713, 4471, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8778, 713, 4471, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8779, 713, 4472, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9213, 748, 4675, 2690, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9214, 748, 4675, 2691, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9215, 748, 4675, 2692, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9216, 748, 4675, 2693, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9217, 748, 4675, 2694, 'Project Title
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9218, 748, 4675, 2695, 'Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom. List the name, title, roles and responsibilities of the contact PI and any other individuals on the project team who will be responsible for oversight of data management and sharing.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9219, 748, 4675, 2696, 'Will data management and/or sharing activities be facilitated by individuals outside of the project team?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9220, 748, 4675, 2697, 'If yes, list the individual(s) and their organization(s) and describe their role(s) and responsibilities. Examples include a data coordinating center, institutional librarians, or investigators on other NIH awards (list award numbers, if relevant).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9221, 748, 4676, 2698, 'Will the project be managing and/or sharing data derived from humans?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9222, 748, 4676, 2699, 'Will the individuals from whom the data are collected or derived have provided informed consent for the collection of the data?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No (Describe under what auspices data will or have been collected in the space below)", "value": "No (Describe under what auspices data will or have been collected in the space below)", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9223, 748, 4676, 2700, 'Are there any limitations or restrictions on the sharing and/or secondary use of the collected data? Restrictions may be based on informed consent under which the data were collected or specific legal, regulatory, or policy requirements.
If yes, provide justification, including a description of the data use limitations and the institutional entity or other entity that approved the limitations in the additional comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9224, 748, 4676, 2701, 'Describe what measures will be taken to protect the privacy of participants and the confidentiality of the data. Examples include de-identification, Certificates of Confidentiality, and other protective measures.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9225, 748, 4677, 2702, 'Describe project-associated documentation that will be made accessible to facilitate interpretation of the scientific data and where the document will be shared. Examples include study protocols and data collection instruments.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9226, 748, 4677, 2703, 'Will you be performing secondary analysis of extant data to generate scientific data for this project?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9227, 748, 4677, 2704, 'If yes, describe data source(s) and provide a dataset identifier (if available). For example, Digital object identifier (DOI, accession number, globally unique identifier, etc.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9228, 748, 4677, 2705, 'Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9229, 748, 4677, 2706, 'If no, provide a justification and explain the factors that determine which scientific data will not be shared:
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| Data Type | Brief Description | Organism, Model, or Other Sources | Amount of Data | Standards | Shared Formats | Data Repository | Data Access Type |
| Define each data type add additional rows to describe multiple data types | Summarize how the data of this type will be managed and prepared for sharing | Projected number of participants or samples from which the data will be generated or other appropriate metrics to describe the scale of the data | List the standards that will be applied to the scientific data and associated metadata if standards exist | Formats of data to be submitted to the data repository | Name the repository where scientific data and metadata will be preserved and shared | Examples include open, registered, controlled or enclave |
Use this section to plan for data submission to and sharing from the repositor(ies) listed in the data type section. Consider publication timelines, performance period, and data repository review and release timelines when planning data submissions and communicate through Plan updates if there are major changes to planned timelines. Shared scientific data should be made accessible as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first.
| Data Repository | Expected number and frequency of submissions | Projected timeline for first submission to repository | Projected timeline for last submission to repository | Target timelines for release | Type of persistent IDs that will be used for data releases, to enable findability and citation of shared datasets | If you will be contributing data to a dataset that is already registered with a data repository, provide that ID |
| Name the data repository described in the Data Type section. Add additional rows as necessary. | Releases associated with data underlying publications, other scheduled releases, and remaining scientific data by the end of the performance period. | Samples include dataset-level digital object identifier (DOI), accession number, globally unique identifier. |
Briefly describe the tools, software, and/or code.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9233, 748, 4680, 2710, 'List the repository or location where researchers can access the tools, software and/ or code and how they can or will be accessed. Access examples include open source and freely available, generally available for a fee in the marketplace, available only from the research team.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9234, 748, 4680, 2711, 'If not yet available, provide target timelines for sharing each tool, software, and/or code developed.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9235, 748, 4681, 2712, 'Use this section to provide additional information or context for readers and reviewers of your Data Management and Sharing Plan. Optional Additional Information:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9243, 749, 4682, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9244, 749, 4682, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9245, 749, 4682, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9246, 749, 4682, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9247, 749, 4682, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9248, 749, 4683, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9249, 749, 4683, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9250, 749, 4683, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9251, 749, 4683, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9252, 749, 4683, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9253, 749, 4683, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9254, 749, 4683, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9255, 749, 4683, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9256, 749, 4683, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain if data sharing timelines will not meet expectations of the DMS or other policies, if applicable. Write N/A if timelines will be met per policy.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9257, 749, 4683, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
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Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9259, 749, 4683, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9260, 749, 4683, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9261, 749, 4683, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9262, 749, 4683, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9263, 749, 4684, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9264, 749, 4684, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9265, 749, 4684, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9266, 750, 4685, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9267, 750, 4685, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9268, 750, 4685, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9269, 750, 4685, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9270, 750, 4685, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9271, 750, 4686, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9272, 750, 4686, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9273, 750, 4686, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9274, 750, 4686, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
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Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
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Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
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Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
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List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
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Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
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What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
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Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9282, 750, 4686, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9283, 750, 4686, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
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Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9285, 750, 4686, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9287, 750, 4687, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9288, 750, 4687, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9289, 751, 4688, 3058, 'Type of Plan
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9291, 751, 4688, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9292, 751, 4688, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9293, 751, 4688, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9294, 751, 4689, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9296, 751, 4689, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9297, 751, 4689, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9298, 751, 4689, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9299, 751, 4689, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9300, 751, 4689, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9301, 751, 4689, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
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Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
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What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
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Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9305, 751, 4689, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9306, 751, 4689, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9307, 751, 4689, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9308, 751, 4689, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9309, 751, 4690, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9310, 751, 4690, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9311, 751, 4690, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9312, 752, 4691, 2690, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9313, 752, 4691, 2691, 'Plan Version Number. For example, 1.0.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9314, 752, 4691, 2692, 'Plan Submission Date, MM/DD/YYYY
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9315, 752, 4691, 2693, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9316, 752, 4691, 2694, 'Project Title
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9317, 752, 4691, 2695, 'Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom. List the name, title, roles and responsibilities of the contact PI and any other individuals on the project team who will be responsible for oversight of data management and sharing.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9318, 752, 4691, 2696, 'Will data management and/or sharing activities be facilitated by individuals outside of the project team?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9319, 752, 4691, 2697, 'If yes, list the individual(s) and their organization(s) and describe their role(s) and responsibilities. Examples include a data coordinating center, institutional librarians, or investigators on other NIH awards (list award numbers, if relevant).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9320, 752, 4692, 2698, 'Will the project be managing and/or sharing data derived from humans?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9321, 752, 4692, 2699, 'Will the individuals from whom the data are collected or derived have provided informed consent for the collection of the data?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No (Describe under what auspices data will or have been collected in the space below)", "value": "No (Describe under what auspices data will or have been collected in the space below)", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9322, 752, 4692, 2700, 'Are there any limitations or restrictions on the sharing and/or secondary use of the collected data? Restrictions may be based on informed consent under which the data were collected or specific legal, regulatory, or policy requirements.
If yes, provide justification, including a description of the data use limitations and the institutional entity or other entity that approved the limitations in the additional comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9323, 752, 4692, 2701, 'Describe what measures will be taken to protect the privacy of participants and the confidentiality of the data. Examples include de-identification, Certificates of Confidentiality, and other protective measures.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9324, 752, 4693, 2702, 'Describe project-associated documentation that will be made accessible to facilitate interpretation of the scientific data and where the document will be shared. Examples include study protocols and data collection instruments.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9325, 752, 4693, 2703, 'Will you be performing secondary analysis of extant data to generate scientific data for this project?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9326, 752, 4693, 2704, 'If yes, describe data source(s) and provide a dataset identifier (if available). For example, Digital object identifier (DOI, accession number, globally unique identifier, etc.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9327, 752, 4693, 2705, 'Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9328, 752, 4693, 2706, 'If no, provide a justification and explain the factors that determine which scientific data will not be shared:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9329, 752, 4694, 2707, '
| Data Type | Brief Description | Organism, Model, or Other Sources | Amount of Data | Standards | Shared Formats | Data Repository | Data Access Type |
| Define each data type add additional rows to describe multiple data types | Summarize how the data of this type will be managed and prepared for sharing | Projected number of participants or samples from which the data will be generated or other appropriate metrics to describe the scale of the data | List the standards that will be applied to the scientific data and associated metadata if standards exist | Formats of data to be submitted to the data repository | Name the repository where scientific data and metadata will be preserved and shared | Examples include open, registered, controlled or enclave |
Use this section to plan for data submission to and sharing from the repositor(ies) listed in the data type section. Consider publication timelines, performance period, and data repository review and release timelines when planning data submissions and communicate through Plan updates if there are major changes to planned timelines. Shared scientific data should be made accessible as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first.
| Data Repository | Expected number and frequency of submissions | Projected timeline for first submission to repository | Projected timeline for last submission to repository | Target timelines for release | Type of persistent IDs that will be used for data releases, to enable findability and citation of shared datasets | If you will be contributing data to a dataset that is already registered with a data repository, provide that ID |
| Name the data repository described in the Data Type section. Add additional rows as necessary. | Releases associated with data underlying publications, other scheduled releases, and remaining scientific data by the end of the performance period. | Samples include dataset-level digital object identifier (DOI), accession number, globally unique identifier. |
Briefly describe the tools, software, and/or code.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9332, 752, 4696, 2710, 'List the repository or location where researchers can access the tools, software and/ or code and how they can or will be accessed. Access examples include open source and freely available, generally available for a fee in the marketplace, available only from the research team.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9333, 752, 4696, 2711, 'If not yet available, provide target timelines for sharing each tool, software, and/or code developed.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9334, 752, 4697, 2712, 'Use this section to provide additional information or context for readers and reviewers of your Data Management and Sharing Plan. Optional Additional Information:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9335, 754, 4698, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9336, 754, 4698, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9337, 754, 4698, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9338, 754, 4698, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9339, 754, 4698, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9340, 754, 4699, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9341, 754, 4699, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9342, 754, 4699, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9343, 754, 4699, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9344, 754, 4699, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9345, 754, 4699, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9346, 754, 4699, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9347, 754, 4699, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9348, 754, 4699, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9349, 754, 4699, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9350, 754, 4699, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9351, 754, 4699, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9352, 754, 4699, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9353, 754, 4699, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9354, 754, 4699, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9355, 754, 4700, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9356, 754, 4700, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9357, 754, 4700, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9358, 754, 4699, 3078, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10177, 814, 5236, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10178, 814, 5236, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10179, 814, 5236, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10180, 814, 5237, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10181, 814, 5238, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10182, 814, 5239, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See selecting a Data Repository
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10183, 814, 5239, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10184, 814, 5239, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10185, 814, 5240, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing.
', '', 'NIH Guidance
See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.
Genomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10186, 814, 5240, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10187, 814, 5240, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10188, 814, 5241, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10312, 825, 5333, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10313, 825, 5333, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10314, 825, 5333, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10315, 825, 5333, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10316, 825, 5333, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10317, 825, 5334, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10318, 825, 5334, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10319, 825, 5334, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10320, 825, 5334, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10321, 825, 5334, 3067, 'Element 1: Data Type
Describe DMS Plan Elements 1-6 in the section below with free text. To maximize the use of structured information in writing a Plan (e.g., data types, repositories) with a drop-down menu option, please proceed to the adjacent tab labeled “Research Outputs."
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10322, 825, 5334, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10323, 825, 5334, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10324, 825, 5334, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10325, 825, 5334, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10326, 825, 5334, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10327, 825, 5334, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10328, 825, 5334, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10329, 825, 5334, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10330, 825, 5334, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10331, 825, 5334, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10332, 825, 5334, 3078, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10333, 825, 5335, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10334, 825, 5335, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10335, 825, 5335, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10491, 836, 5401, 3011, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be).
', '', 'NIH Guidance
The final 2023 NIH DMS Policy (NOT-OD-21-013) defines scientific data as the recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
NIMH Guidance
Please check the 2023 NIMH DMS policy (NOT-MH-23-100) for NIMH-specific requirements in addition to the 2023 NIH DMS policy (NOT-OD-21-013).
NIMH expects data sharing plans to also include a description of the standard(s) and/or data dictionaries that will be used to describe the data set, as well as a proposed schedule to validate that the data are compliant with the data dictionary that is being used.
NIMH has certain requirements for these standards such as a set of common data elements (see NOT-MH-20-067 for non-HIV research; for HIV-related research, see NOT-MH-23-105).
The NDA provides an online Data Dictionary with a searchable interface to find data structures that awardees are expected to use for new data collection. The NDA Data Dictionary is updated as researchers extend existing data collection instruments or create new instruments. For more information, see the NDA NIMH Common Data Elements page.
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database.
', '
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
Per the Policy, even those scientific data not used to support a publication are considered to be scientific data and to fall within the final DMS Policy’s scope.
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations for NIMH
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release)
NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database. All data associated with new projects at the NIMH Repository and Genomics Resource will also be deposited in the NDA. Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP).
Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
NIMH Guidance
Investigators should review the planning section of the NIMH Data Archive website, Use of the NDA includes the NDA data harmonization approach for metadata and documentation.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10494, 836, 5402, 3014, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', 'Additional Guidance from DMPTool
Tool(s) and software should be identified; then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
For human clinical and/or MRI data, please refer to the clinical imaging example on the NIMH site, also known as Sample Plan A on the NIH sharing site.
State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and describe how these data standards will be applied. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
NIMH Guidance
Applicants are strongly encouraged to use clinical and phenotypic data collection instruments/data dictionaries that have already been defined rather than create new versions of those data dictionaries. There are several required data collection instruments, mostly related to demographic and sample information, that must be used by all researchers for data harmonization purposes except for HIV-related applications (https://nda.nih.gov/contribute/harmonization-standards.html).
The NIHM Data Archive (NDA) provides its own standards for metadata and data structures. The standards that a PI intends to use for compatibility with the NDA should be briefly described in this section.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data.
Furthermore, if formal standards such as specific imaging or sequencing filetypes, descriptive metadata, collection formats, etc., beyond the NDA standards will be used, that should also be addressed in this Element.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)
', '', 'NIH Guidance
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016. Selecting a Data Repository Page of the NIH sharing website.
NIMH Guidance
Research funded by the NIMH are required to deposit all raw and analyzed data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) from studies involving human subjects into the NIMH Data Archive (NDA).
NIMH Guidance on NIH GDS Policy Considerations
NOT-MH-23-100 requires that the NIMH Data Archive (NDA) serve as the repository for genomic data funded by the NIMH unless the NIMH approves a different data repository during the negotiation of the terms and conditions of the award.
Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP Submission Process). After registration, all data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) will be deposited in the NDA. A link to NDA will be added to the dbGaP registration. Aggregating the genomic data in a single cloud-based data archive will facilitate the re-analysis, replication, and additional analyses of these important data sets. Computational credits may be available to conduct these analyses in the cloud.
All data associated with new projects at the NIMH Repository and Genomics Resource will be deposited in the NDA. Appropriate data will then be transmitted to the NIMH Repository and Genomics Resource for quality control and to allow the research community to identify samples that are relevant to their research efforts.
Additional Guidance from DMPTool
The NIMH notice of data sharing policy does not provide specific guidance on access and preservation of non-human data for the data management and sharing policy. Consult the NIMH data sharing website or the trans-NIH repositories list for further possibilities.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
Additional Guidance from DMPTool
NIMH Data Archive data collections have DOIs to help make the data in them findable and identifiable.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10498, 836, 5404, 3018, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. The NIMH further specifies that data must be shared with the research community when papers using the data have been accepted for publication or at the end of the award period (including the first no cost extension). Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
NIH GDS Policy Considerations
Genomic data is subject to further guidance on release expectations and timelines.
NIMH Guidance
The general expectation is that data from NIMH-funded awards that involve human subjects will be submitted to NDA every 6 months throughout the duration of the award (typically January and July). Awardees will provide a Data Submission Agreement signed by the principal investigator and an institutional business official within 6 months of the notice of award. Although submission does not lead to release of the data, awardees are encouraged to share basic demographic and raw baseline data shortly after data submission to encourage collaborations in the research community.
In addition to regular submission of data associated with an award, awardees are expected to separately submit to NDA the specific data that was used for each resulting publication by creating an NDA Study.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10499, 836, 5405, 3019, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.
', '', 'NIH Guidance
The DMS Policy acknowledges certain factors (i.e., legal, ethical, or technical) that may affect the extent to which scientific data are preserved and shared.
In addition, NOT-OD-22-213 addresses specific considerations about human subjects privacy.
Additional Guidance from DMPTool
This is the section to describe what legal, ethical, or technical issues may require limiting the sharing of your data. Examples may include ethical considerations such as IACUC restrictions on sharing videos or images of procedures. Other nonhuman data factors affecting distribution may include existing legal limits such as data licenses or use agreements or technical limits about the size or structure of the data.
For human data, the NIMH requires the application of privacy protections through the use of the NDA. It is likely to be sufficient in this subsection to say that human ethics require the use of the NIMH Data Archive for privacy.
NIH GDS Policy Considerations
Genomic data may have further considerations to address. The NIH now expects a single data sharing plan at the time of funding application to satisfy both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198). How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', '
The NDA uses controlled access. Summary information on the data shared in NDA will be available in the NDA Query Tool without the need for an NDA user account. To request access to record-level human subject data, researchers must submit a Data Access Request.
Additional guidance from DMPTool
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10501, 836, 5405, 3021, '
Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
NIH Guidance
Effective data stewardship and protection of human research participant (hereinafter “participant”) privacy are achieved in tandem through responsible scientific data sharing practices. Accordingly, NIH has developed supplemental information to the DMS Policy to assist researchers in responsible data sharing by establishing 1) operational principles for protecting participants’ privacy when sharing scientific data, 2) best practices for implementing these principles, and 3) points to consider for choosing whether to designate scientific data for controlled access.
NIMH Guidance
Applicants should also plan to collect the data needed to generate global unique identifiers (GUIDs) for each study subject. The GUID, or Global Unique Identifier, is used as an identifier for a research participant. The GUID provides a secure mechanism to link research participants within and across research project datasets in NDA.
Informed consent documents should describe how study data will be shared with NDA and the research community. The NDA has provided a plain-language description of the NDA as an example when creating informed consent language.
NIMH also expects these additional points to be considered in human subjects research.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10502, 836, 5406, 3022, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
NIH Guidance
This element refers to oversight by the funded institution, rather than by NIH. The DMS Policy does not create any expectations about who will be responsible for Plan oversight at the institution.
Additional guidance from DMPTool
Please confer with your Office of Sponsored Programs, Office of Research, etc., about any additional oversight considerations. Oversight of human data with the NIMH Data Archive may have specific factors to address. All NIMH applicants should consult local campus departments and policies about oversight.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
The Data Management and Sharing Plan must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used.
', '', 'NIMH Guidance
All NIMH DMS Plans must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used. In cases where a data dictionary has been defined in the NIMH Data Archive, the NDA Data Validation and Uploading Tool should be used to ensure your data files are harmonized to the NDA Data Dictionary. Compliance with the approved data management and sharing plan will become a term and condition in the Notice of Award and will be monitored by the NIMH throughout the duration of the award.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10543, 845, 5437, 3058, '
Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10544, 845, 5437, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10545, 845, 5437, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10546, 845, 5437, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10547, 845, 5437, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10548, 845, 5438, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10549, 845, 5438, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10550, 845, 5438, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10551, 845, 5438, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10552, 845, 5438, 3067, 'Element 1: Data Type
Describe DMS Plan Elements 1-6 in the section below with free text. To maximize the use of structured information in writing a Plan (e.g., data types, repositories) with a drop-down menu option, please proceed to the adjacent tab labeled “Research Outputs."
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10553, 845, 5438, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10554, 845, 5438, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10555, 845, 5438, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10556, 845, 5438, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain if data sharing timelines will not meet expectations of the DMS or other policies, if applicable.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10557, 845, 5438, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10558, 845, 5438, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10559, 845, 5438, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10560, 845, 5438, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10561, 845, 5438, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10562, 845, 5438, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10563, 845, 5438, 3078, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10564, 845, 5439, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10565, 845, 5439, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10566, 845, 5439, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12270, 935, 6098, 3533, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be)
NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Policies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12271, 935, 6098, 3534, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12272, 935, 6098, 3535, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12273, 935, 6099, 3536, '2A. State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12274, 935, 6100, 3537, '3A. State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12275, 935, 6101, 3538, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12276, 935, 6101, 3539, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12277, 935, 6101, 3540, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12278, 935, 6102, 3541, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12279, 935, 6102, 3542, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12280, 935, 6102, 3543, '5C. Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12281, 935, 6103, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12282, 936, 6104, 3533, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be)
NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Policies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12283, 936, 6104, 3534, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12284, 936, 6104, 3535, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12285, 936, 6105, 3536, '2A. State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12286, 936, 6106, 3537, '3A. State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12287, 936, 6107, 3538, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12288, 936, 6107, 3539, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12289, 936, 6107, 3540, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12290, 936, 6108, 3541, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12291, 936, 6108, 3542, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12292, 936, 6108, 3543, '5C. Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12293, 936, 6109, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12611, 945, 6198, 3533, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
', '', 'NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Polcies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12612, 945, 6198, 3534, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12613, 945, 6198, 3535, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12614, 945, 6199, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12615, 945, 6200, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12616, 945, 6201, 3538, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12617, 945, 6201, 3539, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12618, 945, 6201, 3540, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12619, 945, 6202, 3541, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing.
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12620, 945, 6202, 3542, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12621, 945, 6202, 3543, '5C. Protections for privacy, rights, and confidentiality of human research participants: if generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12622, 945, 6203, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (13044, 967, 6355, 3685, 'Add one row for each broad type of data to be generated and shared in the project. If data to be generated is not yet known or otherwise does not conform to the columns in this table, explain in the text box below. Be sure to describe any data that will be generated but not shared in Section II and provide a strong justification for why the data cannot be shared. Complete Section VII if generating any genomic data that is subject to the NIH Genomic Data Sharing (GDS) policy.
', '', 'If data to be generated is not yet known or otherwise does not conform to the columns in this table, delete the table and write in an explanation of extenuating circumstances instead.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (85, 16, 85, 2574, 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'Help with a data sharing plan:
The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
Explain whether the research being considered for funding involves human data, non-human data, or both.
', '', 'Information to be included in this section:
Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
', '', 'For human genomic data, investigators are expected to register all studies in the database of Genotypes and Phenotypes (dbGaP) by the time data cleaning and quality control measures begin in addition to submitting the data to the relevant NIH-designated data repository (e.g., dbGaP, Gene Expression Omnibus (GEO), Sequence Read Archive (SRA), the Cancer Genomics Hub) after registration.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
Data in unrestricted-access repositories (e.g., The 1000 Genomes Project) are publicly available to anyone. Controlled-access data (e.g., data in dbGaP) are made available for secondary research only after investigators have obtained appropriate approval to use the requested data for their proposed project.
Provide a timeline for sharing data in a timely manner.
', '', 'In general, NIH will release human genomic data no later than six months after the data have been submitted to NIH-designated data repositories and cleaned, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination of research findings. Investigators should make non-human genomic data publicly available no later than the date of initial publication. However, availability before publication may be expected for certain data, projects (e.g., data from projects with broad utility as a resource for the scientific community such as microbial population-based genomic studies), or by the funding NIH IC.
Note: The Supplemental Information to the GDS Policy provides expectations for the timelines of data submission and release based on the level of data processing, and additional information about the data levels.
State whether an Institutional Review Board (IRB) or analogous review body has reviewed the genomic data sharing aspects of your project, or provide a timeline for such review.
', '', 'IRB review of the investigator’s proposal for data submission is an element of the Institutional Certification which assures that the proposal for data submission and sharing is appropriate. Please keep in mind that an Institutional Certification is generally required for extramural investigators prior to NIH grant award along with other Just- in-Time information or finalization of a contract. For NIH intramural investigators, an Institutional Certification memorandum should be completed and sent from the SD, or delegate, to the IC Genomic Program Administrator (GPA) before research is begun, whenever possible.
Points to Consider for Institutions and Institutional Review Boards in Developing Institutional Certifications for Submitting Human Data under the Genomic Data Sharing Policy.
Describe the appropriate use of the data.
', '', 'NIH-GDS: Appropriate uses of the data:
Under the GDS Policy, data is expected to be shared for broad research purposes. If such use of the data is not appropriate, as expressed in informed consent documents of the research participants whose data are included in the dataset, any limitations on the data use should be described in the Institutional Certification. NIH provides standard language (see Links tab for URL) to guide the development of data use limitations.
Explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing .
', '', 'NIH-GDS: Request for an exception to submission:
If submission of human data generated in the study would not be appropriate because the Institutional Certification (see Links tab for URL) criteria cannot be met, the investigator should explain why in the genomic data sharing plan and describe an alternative mechanism for data sharing. If the funding IC grants an exception to submission, the research will be registered in dbGaP and the reason for the exception and the alternative sharing plan will be described. For NIH intramural studies, the NIH Deputy Director for Intramural Research will make the final decision on the exception request, after the IC has made its determination.
The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
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Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Database of Genotypes and Phenotypes (dbGaP)
NCBI GEO Gene Expressioin Omnibus.https://www.ncbi.nlm.nih.gov/geo/
NCBI SRA Sequence Read Archive. https://www.ncbi.nlm.nih.gov/sra
NIH National Cancer Institute. Genomic Data Commons. https://gdc.cancer.gov/
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1246, 180, 858, 2570, 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
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Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1248, 180, 860, 2573, 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
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Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'Proposed Text:
"Grantees should note that, under the NIH Grants Policy Statement, they are required to keep the data for 3 years following closeout of a grant or contract agreement. NIH expects the timely release and sharing of data to be no later than the acceptance for publication of the main findings from the final dataset.
It is the responsibility of the investigators, their Institutional Review Board (IRB), and their institution to protect the rights of subjects and the confidentiality of the data. Prior to sharing, data should be redacted to strip all identifiers, and effective strategies should be adopted to minimize risks of unauthorized disclosure of personal identifiers. Researchers who are planning clinical trials and intend to share the resulting data should think carefully about the study design, the informed consent documents, and the structure of the resulting dataset prior to the initiation of the study. Investigators who are working for or who are themselves covered entities under the Health Insurance Portability and Accountability Act (HIPAA) must consider issues related to the Privacy Rule. See linked guidance for more information regarding proprietary data.
Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based" (NIH Data Sharing Policy and Implementation Guidance)."
Original Text:
Help with a data sharing plan:
The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
NIH Data Standards and Common Data Elements Resource Guide (.doc)
NIH Common Data Element (CDE) Resource Portal. https://www.nlm.nih.gov/cde/
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', '', 'The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
NIH Data Standards and Common Data Elements Resource Guide (.doc)
NIH Common Data Element (CDE) Resource Portal. https://www.nlm.nih.gov/cde/
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2451, 253, 1426, 2568, 'The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
', '', 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
', '', 'Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
', '', 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
', '', 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
', '', 'Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
', '', 'Investigators seeking $500,000 or more in direct costs in any year should include a description of how final research data will be shared, or explain why data sharing is not possible.
', '', 'The precise content of the data-sharing plan will vary, depending on the data being collected and how the investigator is planning to share the data. Consider the following:
Selecting a Data Repository
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThe method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5613, 506, 3195, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.Selecting a Data Repository
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5716, 517, 3245, 2579, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5717, 517, 3245, 2580, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5718, 517, 3245, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5724, 518, 3246, 2579, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5725, 518, 3246, 2580, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5726, 518, 3246, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5732, 519, 3247, 2579, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5733, 519, 3247, 2580, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5734, 519, 3247, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.The method for sharing that an investigator selects is likely to depend on several factors, including the sensitivity of the data, the size and complexity of the dataset, and the volume of requests anticipated. Investigators sharing under their own auspices may simply mail a CD with the data to the requestor, or post the data on their institutional or personal Website. Although not a condition for data access, some investigators sharing under their own auspices may form collaborations with other investigators seeking their data in order to pursue research of mutual interest. Others may simply share the data by transferring them to a data archive facility to distribute more widely to interested users, to maintain associated documentation, and to meet reporting requirements. Data archives can be particularly attractive for investigators concerned about a large volume of requests, vetting frivolous or inappropriate requests, or providing technical assistance for users seeking help with analyses.
There are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data (PDF)
Alternatively, researchers may want to add their data to a data archive or a data enclave. Datasets that cannot be distributed to the general public, for example, because of participant confidentiality concerns, third-party licensing or use agreements that prohibit redistribution, or national security considerations, can be accessed through a data enclave. A data enclave provides a controlled, secure environment in which eligible researchers can perform analyses using restricted data resources.
Investigators may also wish to develop a "mixed mode" for data sharing that allows for more than one version of the dataset and provides different levels of access depending on the version. For example, a redacted dataset could be made available for general use, but stricter controls through a data enclave would be applied if access to more sensitive data were required.
Investigators will need to determine which method of data sharing is best for their particular dataset. The Data Sharing Workbook (PDF - 75 KB) or (MS Word - 74 KB) provides information and examples of how others have shared data.
From: NIH Data Sharing Policy and Implementation Guidance
It is NIH policy that the results and accomplishments of the activities that it funds should be made available to the public. PD/PIs and recipient organizations are expected to make the results and accomplishments of their activities available to the research community and to the public at large. (See also Availability and Confidentiality of Information-Confidentiality of Information-Access to Research Data in Part I for policies related to providing access to certain research data at public request.) If the outcomes of the research result in inventions, the provisions of the Bayh-Dole Act of 1980, as implemented in 37 CFR 401, apply.
NIH Data Sharing PoliciesThere are several mechanisms for data sharing that investigators can use. For example, investigators sharing under their own auspices should consider using a data-sharing agreement to impose appropriate limitations on users. Such an agreement usually indicates the criteria for data access, whether or not there are any conditions for research use, and can incorporate privacy and confidentiality standards to ensure data security at the recipient site and prohibit manipulation of data for the purposes of identifying subjects. Many examples of data sharing agreements for specific datasets are available on the Internet, including the following:
AHRQ National Inpatient Sample
Russian Longitudinal Monitoring Survey
Center for Medicare and Medicaid Services Data
Taken from: NIH Data Sharing Policy and Implementation Guidance
Regardless of the mechanism used to share data, each dataset will require documentation. (Some fields refer to data documentation by other terms, such as metadata or codebooks). Proper documentation is needed to ensure that others can use the dataset and to prevent misuse, misinterpretation, and confusion. Documentation provides information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, and the like. The precise content of documentation will vary by scientific area, study design, the type of data collected, and characteristics of the dataset.
It is appropriate for scientific authors to acknowledge the source of data upon which their manuscript is based. Many investigators include this information in the methods and/or reference sections of their manuscripts. Journals generally include an acknowledgement section, in which the authors can recognize people who helped them gain access to the data. Authors using shared data should check the policies of the journal to which they plan to submit to determine the precise location in the manuscript for such acknowledgement. Most journals now expect that DNA and amino acid sequences that appear in articles will be submitted to a sequence database before publication. From NIH Data Sharing Policy and Implementation Guidance.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5902, 529, 3335, 2579, 'What file formats will you use for your data, and why?', '', 'Given the breadth and variety of science that NIH supports, neither the precise content for the data documentation, nor the formatting, presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. It would be helpful for members of multiple disciplines and their professional societies to discuss data sharing, determine what standards and best practices should be proposed, and create a social environment that supports data sharing. presentation, or transport mode for data is stipulated. What is sensible in one field or one study may not work at all for others. From NIH Data Sharing Policy and Implementation Guidance', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5903, 529, 3335, 2580, 'What transformations will be necessary to prepare data for preservation/data sharing?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5904, 529, 3335, 2581, 'Do you need funding for the implementation of this data sharing plan?', '', 'Applicants may request funds in their application for data sharing. If funds are being sought, the applicant should address the financial issues in the budget and budget justification sections. Some investigators have more experience than others in estimating costs associated with preparing the dataset and associated documentation, and providing support to data users. As investigators gain experience with the process, their ability to estimate costs will improve. Investigators working with archives can get help with data preparation and cost estimation. Investigators who are concerned about paying for data-sharing costs at the end of their grant can make prior arrangements with archives. Investigators facing considerable delays in the preparation of the final dataset for sharing should consult with the NIH program about how to manage this situation, such as requesting a no-cost extension.The GDS Policy applies to all NIH-funded research that generates large-scale human or non-human genomic data as well as the use of these data for subsequent research. Large-scale data include genome-wide association studies (GWAS), single nucleotide polymorphisms (SNP) arrays, and genome sequence, transcriptomic, metagenomic, epigenomic, and gene expression data, irrespective of funding level and funding mechanisms (e.g. grant, contract, cooperative agreement, or intramural support). NIH Institute or Centers (IC) may expect submission of data from smaller scale research projects based on the state of the science, the programmatic priorities of the IC funding the research, and the utility of the data for the research community.
', '', 'Identify the data repositories to which the data will be submitted, and for human data, whether the data will be available through unrestricted or controlled-access.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time that data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data respositiories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data respository in addition to an NIH-designated data respository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
', '', 'Investigators should submit large-scale genomic data as well as relevant associated data (e.g. phenotype and exposure data) to an NIH-designated data repository in a timely manner. Investigators should also submit any information necessary to interpret the submitted genomic data, such as study protocols, data instruments and survey tools. Genomic data undergo different levels of data processing, which provides the basis for NIHs expectations for data submission and timelines for the release of the data for access by investigators. These expectations and timelines are provided in the Supplemental Information. In general, NIH will release data submitted to NIH-designated data repositories no later than six months after the initial data submissions begins, or at the time of acceptance of the first publication, whichever occurs first, without restrictions on publication or other dissemination.
', '', 'Respect for, and protection of the interests of, research participants are fundamental to NIHs stewardship of human genomic data. The informed consent under which the data or samples were collected is the basis for the submitting institution to determine the appropriateness of data submission to NIH-designated data repositories, and whether the data should be available through unrestricted or controlled access.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', 'In cases where data submission to an NIH-designated data repository is not appropriate, that is, the Institutional Certification criteria cannot be met, investigators should provide a justification for any data submission exceptions requested in the funding application or proposal. The funding IC may grant an exception to submitting relevant data to NIH, and the investigator would be expected to develop an alternate plan to share data through other mechanisms.
', '', 'NIH encourages patenting of technology suitable for subsequent private investment that may lead to the development of products that address public needs without impeding research. However, it is important to note that naturally occurring DNA sequences are not patentable in the U.S. Therefore, basic sequence data and certain related information (e.g. genotypes, haplotypes, p-values, allele frequencies) are pre-competitive. Such data made available through NIH-designated data repositories, and all conclusions derived directly from them, should remain freely available, without any licensing requirements.
NIH encourages broad use of NIH-funded genomic data that is consistent with a responsible approach to management of intellectual property derived from downstream discoveries, as outlined in the NIH Best Practices for the Licensing of Genomic Inventions and Section 8.2.3. Sharing Research Resources, of the NIH Grants Policy Statement. NIH discourages the use of patents to prevent the use of or to block access to genomic or genotype-phenotype data developed with NIH support.
', '', 'The file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6964, 600, 3873, 3537, 'An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6965, 600, 3874, 3538, 'The name of the repository(ies) where scientific data and metadata arising from the project will be archived.', '', 'NIH GuidanceSelecting a Data Repository
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6966, 600, 3874, 3539, 'How the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', '', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6967, 600, 3874, 3540, 'When the scientific data will be made available to other users (i.e., the larger research community, institutions, and/or the broader public) and for how long.', '', 'NIH GuidanceData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6968, 600, 3875, 3541, 'Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
', 'For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (6970, 600, 3876, 3544, 'Indicate how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom (e.g., titles, roles).', '', 'NIH Guidance
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
Additional Guidance
List the roles responsible for data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Include the name (if available), title, affiliation, and ORCIDs where possible.
If this is a collaborative project across institutions, explain how data management tasks will be addressed across partners.
Identify which individual (or role) will be responsible for implementing, updating, and revising the DMSP.
Explain how the necessary resources (for example personnel time) to prepare the data for sharing/preservation have been budgeted. Consider and justify any resources needed to adhere to the DMP. These may include curating data and developing documentation, infrastructure necessary to provide local management and preservation, and data deposit fees.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7198, 611, 3972, 3533, 'A general summary of the types and estimated amount of scientific data to be generated and/or used in the research. Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be)', '', 'NIH GuidanceThe file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7202, 611, 3974, 3537, 'An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7203, 611, 3975, 3538, 'The name of the repository(ies) where scientific data and metadata arising from the project will be archived.', '', 'NIH GuidanceSelecting a Data Repository
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7204, 611, 3975, 3539, 'How the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', '', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7205, 611, 3975, 3540, 'When the scientific data will be made available to other users (i.e., the larger research community, institutions, and/or the broader public) and for how long.', '', 'NIH GuidanceData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7206, 611, 3976, 3541, 'Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
', 'For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
For researchers selecting controlled access repositories
Given the sensitive nature of the dataset, de-identified human subjects data will be made available in ________ data repository, which restricts access to the data to qualified investigators with an appropriate research question who sign a data use agreement. [Describe data repository access methods and security measures].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (7208, 611, 3977, 3544, 'Indicate how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom (e.g., titles, roles).', '', '
NIH Guidance
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
Additional Guidance
List the roles responsible for data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Include the name (if available), title, affiliation, and ORCIDs where possible.
If this is a collaborative project across institutions, explain how data management tasks will be addressed across partners.
Identify which individual (or role) will be responsible for implementing, updating, and revising the DMSP.
Explain how the necessary resources (for example personnel time) to prepare the data for sharing/preservation have been budgeted. Consider and justify any resources needed to adhere to the DMP. These may include curating data and developing documentation, infrastructure necessary to provide local management and preservation, and data deposit fees.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8616, 693, 4394, 2568, 'Identify the repository or repositories where the investigator plans to submit genomic data.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data repositories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data repository in addition to an NIH-designated data repository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8620, 693, 4398, 2572, 'Describe any limitations on the use of the data. These limitations should be decided by the submitting investigator and their institution, in consultation with the IRB or equivalent body. They should be based on the language in the informed consent form or the recommendations of an IRB or equivalent body.The file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8639, 696, 4408, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceSelecting a Data Repository
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8640, 696, 4408, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', '', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8641, 696, 4408, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long dataData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8642, 696, 4409, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'Additional GuidanceCertain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
Issues to consider:
For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
For researchers selecting controlled access repositories
Given the sensitive nature of the dataset, de-identified human subjects data will be made available in ________ data repository, which restricts access to the data to qualified investigators with an appropriate research question who sign a data use agreement. [Describe data repository access methods and security measures].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8644, 696, 4410, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by
NIH Guidance
This section should address titles and roles overseeing data management and sharing, within the investigator team or as key personnel.
Personnel costs required to perform the types of data management and sharing activities are allowable. Examples of costs may include time and effort for data curation processes; local specialized infrastructure (only those not covered by institutional F&A costs); or fees for preserving and sharing data. Reasonable, allowable costs for management and sharing may be included in NIH budget requests. Funds for these activities must be spent during the performance period, even for scientific data and metadata preserved and shared beyond the award period. See NIH’s supplementary guidance on allowable costs for data management and sharing.
Additional Guidance
List the roles responsible for data capture, metadata production, data quality, storage and backup, data archiving, and data sharing. Include the name (if available), title, affiliation, and ORCIDs where possible.
If this is a collaborative project across institutions, explain how data management tasks will be addressed across partners.
Identify which individual (or role) will be responsible for implementing, updating, and revising the DMSP.
Explain how the necessary resources (for example personnel time) to prepare the data for sharing/preservation have been budgeted. Consider and justify any resources needed to adhere to the DMP. These may include curating data and developing documentation, infrastructure necessary to provide local management and preservation, and data deposit fees.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8645, 696, 4409, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8646, 698, 4411, 2568, 'Identify the repository or repositories where the investigator plans to submit genomic data.
Investigators should register all studies with human genomic data that fall within the scope of the GDS Policy in dbGaP by the time data cleaning and quality control measures begin. After registration in dbGaP, investigators should submit the data to the relevant NIH-designated data repository (e.g., dbGaP, GEO, SRA, the Cancer Genomics Hub). NIH-designated data repositories need not be the exclusive source for facilitating the sharing of genomic data, that is, investigators may also elect to submit data to a non-NIH-designated data repository in addition to an NIH-designated data repository. However, investigators should ensure that appropriate data security measures are in place, and that confidentiality, privacy, and data use measures are consistent with the GDS Policy.
Non-human data may be made available through any widely used data repository, whether NIH- funded or not, such as GEO, SRA, Trace Archive, Array Express, Mouse Genome Informatics, WormBase, the Zebrafish Model Organism Database, GenBank, European Nucleotide Archive, or DNA Data Bank of Japan.
For research that falls within the scope of the GDS Policy, submitting institutions, through their Institutional Review Boards (IRBs), privacy boards, or equivalent bodies, are to review the informed consent materials to determine whether it is appropriate for data to be shared for secondary research use. Specific considerations may vary with the type of study and whether the data are obtained through prospective or retrospective data collections. NIH provides additional information on issues related to the respect for research participant interests its "Points to Consider for IRB"s and Institutions in their Review of Data Submission Plans for Institutional Certifications" (updated in 2016 to "Points to Consider for Institutions and Institutional Review Boards in Submission and Secondary Use of Human Genomic Data under the National Institutes of Health Genomic Data Sharing Policy").
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8650, 698, 4415, 2572, 'Describe any limitations on the use of the data. These limitations should be decided by the submitting investigator and their institution, in consultation with the IRB or equivalent body. They should be based on the language in the informed consent form or the recommendations of an IRB or equivalent body.The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data.
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
', 'To facilitate interpretation of the data, ______ [e.g., metadata, documentation, protocols, data collection instruments] will be shared and associated with the relevant datasets.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8670, 704, 4429, 3536, '
State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified; plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc] data will be made available in _____ [csv, txt, dicom, etc] format and will not require the use of specialized tools to be accessed or manipulated.
If specialized tools are needed to access or manipulate the data:
_____ [Data type] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8671, 704, 4430, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'To facilitate their efficient use, all of our data and materials will be structured and described using the following standards:
If there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g. implementation in data repositories, utility in combining/reusing datasets]
If there are not formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices.
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g. the meaning of variable names, codes, information about missing data, other metadata etc] will be recorded in ____ [data dictionaries/codebooks] that will be accessible to the research team and will subsequently be shared alongside final datasets.
Information about our research process, including the details of our analysis pipeline will be maintained contemporaneously, using ____ [lab notebooks, protocols, etc]. This information will be accessible to all members of the research team and will be shared alongside our data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8672, 704, 4431, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceGenomic data has further guidance and considerations to address in the Plan.
Additional Guidance
See NOT-OD-21-016 and other guidance on selecting a repository, for details on repository considerations. In brief, the first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
Sample Language for Dryad Data Repository
Dataset(s) resulting from this research will be shared via the generalist repository Dryad, which provides metadata, persistent identifiers (i.e., DOIs), and long-term access. Dryad is the institutional data repository supported by the University of California and all data is shared under a CC0 waiver, which makes the dataset(s) publicly available. Data will be made available as soon as possible or at the time of associated publication. Dryad datasets are backed up to Merritt, the UC’s CoreTrustSeal-certified digital repository, for long-term storage and accessibility. Procedures in place to ensure dataset preservation include storage of data files in multiple geographic locations, regular audits for fixity and authenticity, and succession plans in the event of repository closure.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8673, 704, 4431, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'The _________ [Insert repository name] provides metadata, persistent identifiers (i.e., insert whether DOI, handles, other), and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information] OR through a request process __________ [Insert information about request process].', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8674, 704, 4431, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceData will be made available as soon as possible or at the time of associated publication.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8675, 704, 4432, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data-sharing plan at the time of funding application to satisfy both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional GuidanceSome data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8676, 704, 4432, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8677, 704, 4432, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data they should be described here.
Issues to consider:
For researchers working with human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ method. [Describe de-identification method, noting any other applicable laws or policies such as HIPAA].
For researchers selecting controlled access repositories
Given the sensitive nature of the dataset, de-identified human subjects data will be made available in ________ data repository, which restricts access to the data to qualified investigators with an appropriate research question who sign a data use agreement. [Describe data repository access methods and security measures].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8678, 704, 4433, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', '
Additional Guidance:
Describe how and by whom compliance with this Plan will be managed. If roles will include the addition of study personnel for data management oversight, see NIH’s supplementary guidance on allowable costs for data management and sharing. Budget considerations are not addressed in this section but instead, you will request funds towards DMS costs as a line item in the budget form, and provide a brief summary of the DMS Plan and a description of the requested DMS costs in the budget justification.
', 'The following individuals [or just the position titles if unknown] will be responsible for data collection, management, storage, retention, and dissemination of project data, including updating and revising the Data Management and Sharing Plan when necessary.
Sample Language for budgeting requirements
This project includes the following costs associated with data management and sharing.
For data curation and the development of related documentation, the project is requesting $______. These funds will allow us to prepare data for sharing including de-identification of data, the incorporation of metadata to ensure discoverability and the data transfer process to ______repository for preservation and access. An additional cost of $ ______ is required to cover data deposit fees for ______ repository, which will cover ______ years of hosting.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8718, 708, 4443, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8719, 708, 4443, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8720, 708, 4443, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8721, 708, 4444, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8722, 708, 4445, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8723, 708, 4446, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceNIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Genomic data has further guidance and considerations to address in the Plan.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8724, 708, 4446, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8725, 708, 4446, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8726, 708, 4447, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8727, 708, 4447, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8728, 708, 4447, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8729, 708, 4448, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Additional DMPTool Guidance:
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8730, 709, 4449, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8731, 709, 4449, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8732, 709, 4449, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8733, 709, 4450, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8734, 709, 4451, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8735, 709, 4452, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceNIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Genomic data has further guidance and considerations to address in the Plan.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8736, 709, 4452, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8737, 709, 4452, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8738, 709, 4453, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8739, 709, 4453, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8740, 709, 4453, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8741, 709, 4454, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8768, 713, 4467, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8769, 713, 4467, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8770, 713, 4467, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8771, 713, 4468, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8772, 713, 4469, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8773, 713, 4470, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)', '', 'NIH GuidanceNIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8774, 713, 4470, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8775, 713, 4470, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8776, 713, 4471, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.', '', 'NIH GuidanceGenomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8777, 713, 4471, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8778, 713, 4471, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (8779, 713, 4472, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9214, 748, 4675, 2691, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9215, 748, 4675, 2692, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9216, 748, 4675, 2693, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9217, 748, 4675, 2694, 'Project Title
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9218, 748, 4675, 2695, 'Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom. List the name, title, roles and responsibilities of the contact PI and any other individuals on the project team who will be responsible for oversight of data management and sharing.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9219, 748, 4675, 2696, 'Will data management and/or sharing activities be facilitated by individuals outside of the project team?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9220, 748, 4675, 2697, 'If yes, list the individual(s) and their organization(s) and describe their role(s) and responsibilities. Examples include a data coordinating center, institutional librarians, or investigators on other NIH awards (list award numbers, if relevant).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9221, 748, 4676, 2698, 'Will the project be managing and/or sharing data derived from humans?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9222, 748, 4676, 2699, 'Will the individuals from whom the data are collected or derived have provided informed consent for the collection of the data?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No (Describe under what auspices data will or have been collected in the space below)", "value": "No (Describe under what auspices data will or have been collected in the space below)", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9223, 748, 4676, 2700, 'Are there any limitations or restrictions on the sharing and/or secondary use of the collected data? Restrictions may be based on informed consent under which the data were collected or specific legal, regulatory, or policy requirements.
If yes, provide justification, including a description of the data use limitations and the institutional entity or other entity that approved the limitations in the additional comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9224, 748, 4676, 2701, 'Describe what measures will be taken to protect the privacy of participants and the confidentiality of the data. Examples include de-identification, Certificates of Confidentiality, and other protective measures.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9225, 748, 4677, 2702, 'Describe project-associated documentation that will be made accessible to facilitate interpretation of the scientific data and where the document will be shared. Examples include study protocols and data collection instruments.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9226, 748, 4677, 2703, 'Will you be performing secondary analysis of extant data to generate scientific data for this project?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9227, 748, 4677, 2704, 'If yes, describe data source(s) and provide a dataset identifier (if available). For example, Digital object identifier (DOI, accession number, globally unique identifier, etc.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9228, 748, 4677, 2705, 'Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9229, 748, 4677, 2706, 'If no, provide a justification and explain the factors that determine which scientific data will not be shared:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9230, 748, 4678, 2707, '
| Data Type | Brief Description | Organism, Model, or Other Sources | Amount of Data | Standards | Shared Formats | Data Repository | Data Access Type |
| Define each data type add additional rows to describe multiple data types | Summarize how the data of this type will be managed and prepared for sharing | Projected number of participants or samples from which the data will be generated or other appropriate metrics to describe the scale of the data | List the standards that will be applied to the scientific data and associated metadata if standards exist | Formats of data to be submitted to the data repository | Name the repository where scientific data and metadata will be preserved and shared | Examples include open, registered, controlled or enclave |
Use this section to plan for data submission to and sharing from the repositor(ies) listed in the data type section. Consider publication timelines, performance period, and data repository review and release timelines when planning data submissions and communicate through Plan updates if there are major changes to planned timelines. Shared scientific data should be made accessible as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first.
| Data Repository | Expected number and frequency of submissions | Projected timeline for first submission to repository | Projected timeline for last submission to repository | Target timelines for release | Type of persistent IDs that will be used for data releases, to enable findability and citation of shared datasets | If you will be contributing data to a dataset that is already registered with a data repository, provide that ID |
| Name the data repository described in the Data Type section. Add additional rows as necessary. | Releases associated with data underlying publications, other scheduled releases, and remaining scientific data by the end of the performance period. | Samples include dataset-level digital object identifier (DOI), accession number, globally unique identifier. |
Briefly describe the tools, software, and/or code.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9233, 748, 4680, 2710, 'List the repository or location where researchers can access the tools, software and/ or code and how they can or will be accessed. Access examples include open source and freely available, generally available for a fee in the marketplace, available only from the research team.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9234, 748, 4680, 2711, 'If not yet available, provide target timelines for sharing each tool, software, and/or code developed.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9235, 748, 4681, 2712, 'Use this section to provide additional information or context for readers and reviewers of your Data Management and Sharing Plan. Optional Additional Information:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9243, 749, 4682, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9244, 749, 4682, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9245, 749, 4682, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9246, 749, 4682, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9247, 749, 4682, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9248, 749, 4683, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9249, 749, 4683, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9250, 749, 4683, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9251, 749, 4683, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9252, 749, 4683, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9253, 749, 4683, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9254, 749, 4683, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9255, 749, 4683, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9256, 749, 4683, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain if data sharing timelines will not meet expectations of the DMS or other policies, if applicable. Write N/A if timelines will be met per policy.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9257, 749, 4683, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9258, 749, 4683, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9259, 749, 4683, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9260, 749, 4683, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9261, 749, 4683, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9262, 749, 4683, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9263, 749, 4684, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9264, 749, 4684, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9265, 749, 4684, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9266, 750, 4685, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9267, 750, 4685, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9268, 750, 4685, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9269, 750, 4685, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9270, 750, 4685, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9271, 750, 4686, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9272, 750, 4686, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9273, 750, 4686, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9274, 750, 4686, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9275, 750, 4686, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9276, 750, 4686, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9277, 750, 4686, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9278, 750, 4686, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9279, 750, 4686, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9280, 750, 4686, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9281, 750, 4686, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9282, 750, 4686, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9283, 750, 4686, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9284, 750, 4686, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9285, 750, 4686, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9286, 750, 4687, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9287, 750, 4687, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9288, 750, 4687, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9289, 751, 4688, 3058, 'Type of Plan
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9291, 751, 4688, 3060, 'Plan Submission Date
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9293, 751, 4688, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9294, 751, 4689, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9295, 751, 4689, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9296, 751, 4689, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9297, 751, 4689, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9298, 751, 4689, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9299, 751, 4689, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9300, 751, 4689, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
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List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9302, 751, 4689, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9303, 751, 4689, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
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Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9305, 751, 4689, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
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What type of access will secondary users utilize to access the shared data? Describe if “Other.”
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Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9308, 751, 4689, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
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', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9310, 751, 4690, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9311, 751, 4690, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9312, 752, 4691, 2690, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9313, 752, 4691, 2691, 'Plan Version Number. For example, 1.0.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9314, 752, 4691, 2692, 'Plan Submission Date, MM/DD/YYYY
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9315, 752, 4691, 2693, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9316, 752, 4691, 2694, 'Project Title
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9317, 752, 4691, 2695, 'Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom. List the name, title, roles and responsibilities of the contact PI and any other individuals on the project team who will be responsible for oversight of data management and sharing.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9318, 752, 4691, 2696, 'Will data management and/or sharing activities be facilitated by individuals outside of the project team?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9319, 752, 4691, 2697, 'If yes, list the individual(s) and their organization(s) and describe their role(s) and responsibilities. Examples include a data coordinating center, institutional librarians, or investigators on other NIH awards (list award numbers, if relevant).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9320, 752, 4692, 2698, 'Will the project be managing and/or sharing data derived from humans?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9321, 752, 4692, 2699, 'Will the individuals from whom the data are collected or derived have provided informed consent for the collection of the data?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No (Describe under what auspices data will or have been collected in the space below)", "value": "No (Describe under what auspices data will or have been collected in the space below)", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9322, 752, 4692, 2700, 'Are there any limitations or restrictions on the sharing and/or secondary use of the collected data? Restrictions may be based on informed consent under which the data were collected or specific legal, regulatory, or policy requirements.
If yes, provide justification, including a description of the data use limitations and the institutional entity or other entity that approved the limitations in the additional comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9323, 752, 4692, 2701, 'Describe what measures will be taken to protect the privacy of participants and the confidentiality of the data. Examples include de-identification, Certificates of Confidentiality, and other protective measures.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9324, 752, 4693, 2702, 'Describe project-associated documentation that will be made accessible to facilitate interpretation of the scientific data and where the document will be shared. Examples include study protocols and data collection instruments.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9325, 752, 4693, 2703, 'Will you be performing secondary analysis of extant data to generate scientific data for this project?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9326, 752, 4693, 2704, 'If yes, describe data source(s) and provide a dataset identifier (if available). For example, Digital object identifier (DOI, accession number, globally unique identifier, etc.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9327, 752, 4693, 2705, 'Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9328, 752, 4693, 2706, 'If no, provide a justification and explain the factors that determine which scientific data will not be shared:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9329, 752, 4694, 2707, '
| Data Type | Brief Description | Organism, Model, or Other Sources | Amount of Data | Standards | Shared Formats | Data Repository | Data Access Type |
| Define each data type add additional rows to describe multiple data types | Summarize how the data of this type will be managed and prepared for sharing | Projected number of participants or samples from which the data will be generated or other appropriate metrics to describe the scale of the data | List the standards that will be applied to the scientific data and associated metadata if standards exist | Formats of data to be submitted to the data repository | Name the repository where scientific data and metadata will be preserved and shared | Examples include open, registered, controlled or enclave |
Use this section to plan for data submission to and sharing from the repositor(ies) listed in the data type section. Consider publication timelines, performance period, and data repository review and release timelines when planning data submissions and communicate through Plan updates if there are major changes to planned timelines. Shared scientific data should be made accessible as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first.
| Data Repository | Expected number and frequency of submissions | Projected timeline for first submission to repository | Projected timeline for last submission to repository | Target timelines for release | Type of persistent IDs that will be used for data releases, to enable findability and citation of shared datasets | If you will be contributing data to a dataset that is already registered with a data repository, provide that ID |
| Name the data repository described in the Data Type section. Add additional rows as necessary. | Releases associated with data underlying publications, other scheduled releases, and remaining scientific data by the end of the performance period. | Samples include dataset-level digital object identifier (DOI), accession number, globally unique identifier. |
Briefly describe the tools, software, and/or code.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9332, 752, 4696, 2710, 'List the repository or location where researchers can access the tools, software and/ or code and how they can or will be accessed. Access examples include open source and freely available, generally available for a fee in the marketplace, available only from the research team.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9333, 752, 4696, 2711, 'If not yet available, provide target timelines for sharing each tool, software, and/or code developed.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9334, 752, 4697, 2712, 'Use this section to provide additional information or context for readers and reviewers of your Data Management and Sharing Plan. Optional Additional Information:
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9335, 754, 4698, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9336, 754, 4698, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9337, 754, 4698, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9338, 754, 4698, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9339, 754, 4698, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9340, 754, 4699, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9341, 754, 4699, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9342, 754, 4699, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9343, 754, 4699, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9344, 754, 4699, 3067, 'Element 1: Data Type
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9345, 754, 4699, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9346, 754, 4699, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9347, 754, 4699, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9348, 754, 4699, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9349, 754, 4699, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9350, 754, 4699, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9351, 754, 4699, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9352, 754, 4699, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9353, 754, 4699, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9354, 754, 4699, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9355, 754, 4700, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9356, 754, 4700, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9357, 754, 4700, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (9358, 754, 4699, 3078, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10177, 814, 5236, 3533, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.NIH Guidance
The final DMS Policy has specific definitions for what Scientific Data is, and what proposals are considered to be producing scientific data
Per the Policy, “Even those scientific data not used to support a publication are considered scientific data and within the final DMS Policy’s scope. We understand that a lack of publication does not necessarily mean that the findings are null or negative; however, indicating that scientific data are defined independent of publication is sufficient to cover data underlying null or negative findings.”
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10178, 814, 5236, 3534, 'Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213
NIH GDS Policy Considerations
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release).
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10179, 814, 5236, 3535, 'Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10180, 814, 5237, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10181, 814, 5238, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist', '', 'NIH GuidanceA standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', 'DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10182, 814, 5239, 3538, 'Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See selecting a Data Repository
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
Additional Guidance from DMPTool
See NOT-OD-21-016 and other guidance on selecting a repository for details on repository considerations. In brief, first consideration (option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. Next priority (Option 2A) goes to approved Open Domain-Specific Data Sharing Repositories). If neither of those considerations fit, consider (Option 2B) other potentially suitable options: PubMed Central attachments, approved generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations
If your research is subject to GDS policy, please refer to recommended repositories on the “Where to Submit Genomic Data” page on the NIH sharing site.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10183, 814, 5239, 3539, 'How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10184, 814, 5239, 3540, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.', '', 'NIH GuidanceDMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10185, 814, 5240, 3541, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing.
', '', 'NIH Guidance
See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.
Genomic data may have further considerations to address. The NIH now expects a single data sharing plan at time of funding application satisfies both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198).
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data specifically may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
NIH GDS Policy Considerations
How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10186, 814, 5240, 3542, 'Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10187, 814, 5240, 3543, 'Protections for privacy, rights, and confidentiality of human research participants:Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10188, 814, 5241, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).', '', 'Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10312, 825, 5333, 3058, 'Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10313, 825, 5333, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10314, 825, 5333, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10315, 825, 5333, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10316, 825, 5333, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10317, 825, 5334, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10318, 825, 5334, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10319, 825, 5334, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10320, 825, 5334, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10321, 825, 5334, 3067, 'Element 1: Data Type
Describe DMS Plan Elements 1-6 in the section below with free text. To maximize the use of structured information in writing a Plan (e.g., data types, repositories) with a drop-down menu option, please proceed to the adjacent tab labeled “Research Outputs."
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10322, 825, 5334, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10323, 825, 5334, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10324, 825, 5334, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10325, 825, 5334, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain how data sharing timelines will meet expectations of the DMS or other applicable policies.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10326, 825, 5334, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10327, 825, 5334, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10328, 825, 5334, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10329, 825, 5334, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10330, 825, 5334, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10331, 825, 5334, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10332, 825, 5334, 3078, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10333, 825, 5335, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10334, 825, 5335, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10335, 825, 5335, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10491, 836, 5401, 3011, 'Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be).
', '', 'NIH Guidance
The final 2023 NIH DMS Policy (NOT-OD-21-013) defines scientific data as the recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
NIMH Guidance
Please check the 2023 NIMH DMS policy (NOT-MH-23-100) for NIMH-specific requirements in addition to the 2023 NIH DMS policy (NOT-OD-21-013).
NIMH expects data sharing plans to also include a description of the standard(s) and/or data dictionaries that will be used to describe the data set, as well as a proposed schedule to validate that the data are compliant with the data dictionary that is being used.
NIMH has certain requirements for these standards such as a set of common data elements (see NOT-MH-20-067 for non-HIV research; for HIV-related research, see NOT-MH-23-105).
The NDA provides an online Data Dictionary with a searchable interface to find data structures that awardees are expected to use for new data collection. The NDA Data Dictionary is updated as researchers extend existing data collection instruments or create new instruments. For more information, see the NDA NIMH Common Data Elements page.
NIH Genomic Data Sharing (GDS) Policy Considerations
Check if your research is subject to NIH GDS (Genomic Data Sharing) policy using this criteria and list those data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database.
', '
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
Per the Policy, even those scientific data not used to support a publication are considered to be scientific data and to fall within the final DMS Policy’s scope.
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
Additional Guidance from DMPTool
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations for NIMH
If you are generating genomic data, follow specific sharing requirements (data submission and release expectation) under the NIH GDS policy (five levels of processing and associated expectations for data submission and release)
NIMH expects genomic data to be deposited at the NIMH Data Archive (NDA) unless NIMH agrees to a different database. All data associated with new projects at the NIMH Repository and Genomics Resource will also be deposited in the NDA. Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP).
Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
NIMH Guidance
Investigators should review the planning section of the NIMH Data Archive website, Use of the NDA includes the NDA data harmonization approach for metadata and documentation.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10494, 836, 5402, 3014, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', 'Additional Guidance from DMPTool
Tool(s) and software should be identified; then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). When known, the longevity or period of time for which custom or proprietary tools will be available should be addressed.
In addition, file formats in which data are saved in a digital format can be divided into two general categories.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
For human clinical and/or MRI data, please refer to the clinical imaging example on the NIMH site, also known as Sample Plan A on the NIH sharing site.
State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and describe how these data standards will be applied. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
NIMH Guidance
Applicants are strongly encouraged to use clinical and phenotypic data collection instruments/data dictionaries that have already been defined rather than create new versions of those data dictionaries. There are several required data collection instruments, mostly related to demographic and sample information, that must be used by all researchers for data harmonization purposes except for HIV-related applications (https://nda.nih.gov/contribute/harmonization-standards.html).
The NIHM Data Archive (NDA) provides its own standards for metadata and data structures. The standards that a PI intends to use for compatibility with the NDA should be briefly described in this section.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data.
Furthermore, if formal standards such as specific imaging or sequencing filetypes, descriptive metadata, collection formats, etc., beyond the NDA standards will be used, that should also be addressed in this Element.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived; see Selecting a Data Repository)
', '', 'NIH Guidance
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016. Selecting a Data Repository Page of the NIH sharing website.
NIMH Guidance
Research funded by the NIMH are required to deposit all raw and analyzed data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) from studies involving human subjects into the NIMH Data Archive (NDA).
NIMH Guidance on NIH GDS Policy Considerations
NOT-MH-23-100 requires that the NIMH Data Archive (NDA) serve as the repository for genomic data funded by the NIMH unless the NIMH approves a different data repository during the negotiation of the terms and conditions of the award.
Awardees who are measuring human genomic data are required to register with the Database of Genotypes and Phenotypes (dbGaP Submission Process). After registration, all data (including, but not limited to, clinical, genomic, imaging, and phenotypic data) will be deposited in the NDA. A link to NDA will be added to the dbGaP registration. Aggregating the genomic data in a single cloud-based data archive will facilitate the re-analysis, replication, and additional analyses of these important data sets. Computational credits may be available to conduct these analyses in the cloud.
All data associated with new projects at the NIMH Repository and Genomics Resource will be deposited in the NDA. Appropriate data will then be transmitted to the NIMH Repository and Genomics Resource for quality control and to allow the research community to identify samples that are relevant to their research efforts.
Additional Guidance from DMPTool
The NIMH notice of data sharing policy does not provide specific guidance on access and preservation of non-human data for the data management and sharing policy. Consult the NIMH data sharing website or the trans-NIH repositories list for further possibilities.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Unique Persistent Identifiers: The repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
Additional Guidance from DMPTool
NIMH Data Archive data collections have DOIs to help make the data in them findable and identifiable.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10498, 836, 5404, 3018, 'When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. The NIMH further specifies that data must be shared with the research community when papers using the data have been accepted for publication or at the end of the award period (including the first no cost extension). Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
NIH GDS Policy Considerations
Genomic data is subject to further guidance on release expectations and timelines.
NIMH Guidance
The general expectation is that data from NIMH-funded awards that involve human subjects will be submitted to NDA every 6 months throughout the duration of the award (typically January and July). Awardees will provide a Data Submission Agreement signed by the principal investigator and an institutional business official within 6 months of the notice of award. Although submission does not lead to release of the data, awardees are encouraged to share basic demographic and raw baseline data shortly after data submission to encourage collaborations in the research community.
In addition to regular submission of data associated with an award, awardees are expected to separately submit to NDA the specific data that was used for each resulting publication by creating an NDA Study.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10499, 836, 5405, 3019, 'Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing. See Frequently Asked Questions for examples of justifiable reasons for limiting sharing of data.
', '', 'NIH Guidance
The DMS Policy acknowledges certain factors (i.e., legal, ethical, or technical) that may affect the extent to which scientific data are preserved and shared.
In addition, NOT-OD-22-213 addresses specific considerations about human subjects privacy.
Additional Guidance from DMPTool
This is the section to describe what legal, ethical, or technical issues may require limiting the sharing of your data. Examples may include ethical considerations such as IACUC restrictions on sharing videos or images of procedures. Other nonhuman data factors affecting distribution may include existing legal limits such as data licenses or use agreements or technical limits about the size or structure of the data.
For human data, the NIMH requires the application of privacy protections through the use of the NDA. It is likely to be sufficient in this subsection to say that human ethics require the use of the NIMH Data Archive for privacy.
NIH GDS Policy Considerations
Genomic data may have further considerations to address. The NIH now expects a single data sharing plan at the time of funding application to satisfy both the Genomic Data Sharing (GDS) Policy and the DMS Policy (per NOT-OD-22-198). How to access genomic data varies depending on which repository you selected. Please refer to the Accessing Genomic Data from NIH Repositories page on the NIH sharing site.
', 'All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', '
The NDA uses controlled access. Summary information on the data shared in NDA will be available in the NDA Query Tool without the need for an NDA user account. To request access to record-level human subject data, researchers must submit a Data Access Request.
Additional guidance from DMPTool
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
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Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
NIH Guidance
Effective data stewardship and protection of human research participant (hereinafter “participant”) privacy are achieved in tandem through responsible scientific data sharing practices. Accordingly, NIH has developed supplemental information to the DMS Policy to assist researchers in responsible data sharing by establishing 1) operational principles for protecting participants’ privacy when sharing scientific data, 2) best practices for implementing these principles, and 3) points to consider for choosing whether to designate scientific data for controlled access.
NIMH Guidance
Applicants should also plan to collect the data needed to generate global unique identifiers (GUIDs) for each study subject. The GUID, or Global Unique Identifier, is used as an identifier for a research participant. The GUID provides a secure mechanism to link research participants within and across research project datasets in NDA.
Informed consent documents should describe how study data will be shared with NDA and the research community. The NDA has provided a plain-language description of the NDA as an example when creating informed consent language.
NIMH also expects these additional points to be considered in human subjects research.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10502, 836, 5406, 3022, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
NIH Guidance
This element refers to oversight by the funded institution, rather than by NIH. The DMS Policy does not create any expectations about who will be responsible for Plan oversight at the institution.
Additional guidance from DMPTool
Please confer with your Office of Sponsored Programs, Office of Research, etc., about any additional oversight considerations. Oversight of human data with the NIMH Data Archive may have specific factors to address. All NIMH applicants should consult local campus departments and policies about oversight.
All example DMSPs can be found at the end of the NIMH data sharing page or in the sample plans section of the sharing.nih.gov site.
The Data Management and Sharing Plan must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used.
', '', 'NIMH Guidance
All NIMH DMS Plans must propose a schedule to validate the quality of the data being uploaded so these data are compliant with the data dictionary or other standards that are being used. In cases where a data dictionary has been defined in the NIMH Data Archive, the NDA Data Validation and Uploading Tool should be used to ensure your data files are harmonized to the NDA Data Dictionary. Compliance with the approved data management and sharing plan will become a term and condition in the Notice of Award and will be monitored by the NIMH throughout the duration of the award.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10543, 845, 5437, 3058, '
Type of Plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "New", "value": "New", "selected": 0}, {"label": "Revision", "value": "Revision", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10544, 845, 5437, 3059, 'Plan Version Number
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10545, 845, 5437, 3060, 'Plan Submission Date
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10546, 845, 5437, 3061, 'Point of Contact for DMS plan
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10547, 845, 5437, 3062, 'Project/Application/Protocol ID
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10548, 845, 5438, 3063, 'Does the Genomic Data Sharing (GDS) Policy apply?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10549, 845, 5438, 3064, 'Will the datasets be shared according to GDS policy but no later than the time of publication or end of the project, whichever is sooner?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10550, 845, 5438, 3065, 'Will an NIH-supported repository be selected for data subject to GDS?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10551, 845, 5438, 3066, 'Has an Institutional Certification (IC) been submitted with the application or Just-In-Time that meets GDS criteria?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 4, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10552, 845, 5438, 3067, 'Element 1: Data Type
Describe DMS Plan Elements 1-6 in the section below with free text. To maximize the use of structured information in writing a Plan (e.g., data types, repositories) with a drop-down menu option, please proceed to the adjacent tab labeled “Research Outputs."
Will all scientific data generated by the research project be shared in a data repository that makes data available to the larger research community? If No, explain the rationale that determines which scientific data will not be shared in the comment area below.
', '', 'NIH guidance: Scientific Data is defined as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 5, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10553, 845, 5438, 3068, 'Element 2: Tools, Software, Code
Describe the tools, software, and/or code that are needed to access or manipulate shared scientific data to support replication or reuse, if any.
', '', 'NIH Guidance: Indicate names of the specialized tools needed to access or manipulate each shared respective data type, if any.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 6, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10554, 845, 5438, 3069, 'Element 2: Tools, Software, Code
Describe how researchers can access the tools, software, and/or code listed above. Describe if “Other.”
', '', 'Specify how needed tools can be accessed.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open source", "value": "Open source", "selected": 0}, {"label": "Available for a fee", "value": "Available for a fee", "selected": 0}, {"label": "Restricted availability from a specific source ", "value": "Restricted availability from a specific source ", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 7, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10555, 845, 5438, 3070, 'Element 3: Standards
List data or metadata standards or common data elements that will be used applicable to each data type shared. Write N/A if no existing standards.
', '', 'NIH Guidance: Data standards refer to community-accepted methods of organizing, documenting, and formatting data to aid in data aggregation, sharing, and reuse.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 8, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10556, 845, 5438, 3071, 'Element 4: Data Preservation, Access, and Timelines
Explain if data sharing timelines will not meet expectations of the DMS or other policies, if applicable.
', '', 'NIH Guidance: NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 9, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10557, 845, 5438, 3072, 'Element 4: Data Preservation, Access, and Timelines
What types of persistent identifiers/ indexing methods will be used for data releases, to enable findability and citation of shared datasets?
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 10, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10558, 845, 5438, 3073, 'Element 5: Access, Distribution or Reuse Considerations
Describe any limitations or factors affecting subsequent access, distribution, or reuse of this data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 11, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10559, 845, 5438, 3074, 'Element 5: Access, Distribution or Reuse Considerations
Are there any privacy or informed consent considerations for human data? If Yes, describe including methods to protect privacy and confidentiality.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 12, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10560, 845, 5438, 3075, 'Element 5: Access, Distribution or Reuse Considerations
What type of access will secondary users utilize to access the shared data? Describe if “Other.”
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Open access", "value": "Open access", "selected": 0}, {"label": "Managed access", "value": "Managed access", "selected": 0}, {"label": "Controlled access", "value": "Controlled access", "selected": 0}, {"label": "Data Enclave", "value": "Data Enclave", "selected": 0}, {"label": "Other", "value": "Other", "selected": 0}], "attributes": {"multiple": 0}}', 0, 13, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10561, 845, 5438, 3076, 'Element 6: Compliance
Describe how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom.
', '', 'NIH Guidance: Indicate the data management and sharing lead name and contact information; the frequency and methods that your institution will provide oversight and by whom (e.g., titles, roles and responsibilities).
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 14, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10562, 845, 5438, 3077, 'Element 6: Compliance
Will data management and/or sharing activities be facilitated by individuals outside of the project team? If YES, list individual(s), their organization(s), and describe their role(s) and responsibilities in the comments area below.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "selectBox", "options": [{"label": "Yes", "value": "Yes", "selected": 0}, {"label": "No", "value": "No", "selected": 0}], "attributes": {"multiple": 0}}', 0, 15, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10563, 845, 5438, 3078, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 16, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10564, 845, 5439, 3079, 'If additional policies apply (e.g., Clinical Trials Access Policy, FOA-specific requirements), describe additional information required to meet the policy.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10565, 845, 5439, 3080, 'Provide any additional information or context for readers and reviewers of your Data Management and Sharing Plan.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (10566, 845, 5439, 3081, 'Please proceed to the Research Outputs tab in this application to provide details about the data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "text", "attributes": {"pattern": "^.+$", "maxLength": 1000, "minLength": 0}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12270, 935, 6098, 3533, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be)
NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Policies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12271, 935, 6098, 3534, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12272, 935, 6098, 3535, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12273, 935, 6099, 3536, '2A. State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12274, 935, 6100, 3537, '3A. State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12275, 935, 6101, 3538, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12276, 935, 6101, 3539, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12277, 935, 6101, 3540, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12278, 935, 6102, 3541, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12279, 935, 6102, 3542, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12280, 935, 6102, 3543, '5C. Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12281, 935, 6103, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12282, 936, 6104, 3533, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
Describe data in general terms that address the type and amount/size of scientific data expected to be collected and used in the project (e.g., 256-channel EEG data and fMRI images from ~50 research participants). Descriptions may indicate the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing that has occurred (i.e., how raw or processed the data will be)
NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Policies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12283, 936, 6104, 3534, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12284, 936, 6104, 3535, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12285, 936, 6105, 3536, '2A. State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12286, 936, 6106, 3537, '3A. State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12287, 936, 6107, 3538, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12288, 936, 6107, 3539, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12289, 936, 6107, 3540, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12290, 936, 6108, 3541, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12291, 936, 6108, 3542, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12292, 936, 6108, 3543, '5C. Protections for privacy, rights, and confidentiality of human research participants:
If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12293, 936, 6109, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12611, 945, 6198, 3533, '1A.Types and amount of scientific data expected to be generated in the project: Summarize the types and estimated amount of scientific data expected to be generated in the project.
', '', 'NIH Guidance
The 2023 NIH DMS Policy (NOT-OD-21-013) applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. NIH defines scientific data as data commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data does not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects such as laboratory specimens.
To determine if the DMS policy applies to your research, check out the complete list of NIH activity codes subject to the DMS Policy as well as your funding opportunity.
You may be subject to additional sharing policies. To find out more, check the list of NIH Institute and Center Data Sharing Polcies and/or use the decision tool Which Policies Apply to My Research? This may result in writing a separate Resource Sharing Plan (e.g., Model Organisms or Research Tools) or adding special considerations required by ICs (e.g. validation schedule for NIMH, DMPTool has a separate NIH-NIMH template to incorporate this) or other policies (e.g. Clinical Trial Dissemination Policy) into relevant parts of a DMS plan.
In this section of the Plan, describe data in general terms that address the type, source and amount/size of scientific data expected. Descriptions may indicate data modality, level of aggregation, and/or level of data processing.
NIH Genomic Data Sharing (GDS) Policy Considerations
Use this criteria to determine if your research is subject to NIH GDS (Genomic Data Sharing) policy. List data and the levels of processing here.
Individual NIH Institutes and Centers (IC) may have additional expectations or requirements for genomic data sharing as well. Please check the IC-specific genomic data sharing requirements.
The NIH now expects genomic data to use a single data sharing plan for both the NIH Genomic Data Sharing Policy (GDS Policy) and the NIH Policy for Data Management and Sharing (DMS Policy) as per NOT-OD-22-198. No separate GDS plan will be accepted by NIH.
', 'DMPTool fill-in-the-blank prompt
This project will produce _________ [Data type, e.g., imaging, sequencing, experimental measurements] data generated/obtained from __________ [Data modality, e.g., instrument, method, survey, experiment, data source]. Data will be collected from ___ [number] of research participants/specimens/experiments, generating ___ [number] datasets totaling approximately ___ [amount of data] in size. The following data files will be used or produced in the course of the project: ______ [list input data files, intermediate files, and final, post-processed files]. Raw data will be transformed by ____ [analysis, method], and the subsequent processed dataset used for statistical analysis. To protect research participant identities, ___________ [e.g., individual, aggregated, summarized] data will be made available for sharing.
If working with human subjects, consider adding: Data collection will be performed at clinical sites in the ____ [location] area(s) with ____ [population(s) being studied; i.e., T2 diabetes].
Sample answer from DMPTool: Basic sciences data
In this proposed project, data will be generated via the following methods: cell culture, light microscopy, confocal microscopy, real-time quantitative polymerase chain reaction (PCR), and stereological counting techniques. This data will be collected from a minimum of 3 independent experiments, with each independent experiment consisting of 3 groups, Wild-type (Rest+/+), heterozygous (Rest+/–), and homozygous (Rest–/–) from both embryonic stem (ES) cells and the corresponding neural stem/progenitor (NS/P) cells. The total size of the data collected is projected to be 300 GB.
We expect to generate the following data file types and formats during this project: Carl Zeiss microscopic image file (.CZI), images (.TIFF), tabular (.CSV), and Affymetrix GeneChip files (.CEL).
Raw data files will be analyzed to generate CSV files containing counts of cell type, total number of stem cells, and to enable statistical analysis.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12612, 945, 6198, 3534, '1B. Scientific data that will be preserved and shared, and the rationale for doing so: Describe which scientific data from the project will be preserved and shared and provide the rationale for this decision.
', '', 'NIH Guidance
NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors that may affect the extent to which scientific data are preserved and shared. Provide the rationale for these decisions.
If human subjects data will be collected and only de-identified subsets are to be shared, consider specific de-identification approaches that fit the population and purposes. Guidance on protecting privacy is at NOT-OD-22-213.
NIH GDS Policy Considerations (For data subject to the GDS policy)
Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.
', 'Based on _______ [ethical, legal, technical] considerations, only the following data produced in the course of the project will be preserved and shared: ____ [list subsets of the data to be shared]
OR
All data produced in the course of the project will be preserved and shared.
Addendum to DMPTool fill-in-the-blank prompt: Add the following for working with human data:
The final dataset will include _______[e.g., self-reported demographic and behavioral data from interviews with participants and laboratory data from blood and urine specimens provided]. We will share de-identified individual-participant level (IPD) data. Appropriate measures such as _______ [describe specific de-identification practices to be used] will be used for data de-identification and sharing, and informed consent forms will reflect those plans.
Sample answer from DMPTool: Minimal answer when most data will be shared openly
In this proposed project, the cleaned, item-level spreadsheet data for all variables will be shared openly, along with example quantifications and transformations from initial raw data. Final files used to generate specific analyses to answer the Specific Aims and related results will also be shared. The rationale for sharing only cleaned data is to foster ease of data reuse.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12613, 945, 6198, 3535, '1C. Metadata, other relevant data, and associated documentation: Briefly list the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.
', '', 'NIH Guidance
In addition to the documentation examples, consider metadata that will provide additional information intended to make scientific data interpretable and reusable (e.g., date, independent sample and variable construction and description, methodology, data provenance, data transformations, any intermediate or descriptive observational variables).
DMPTool fill-in-the-blank prompt basics
To facilitate interpretation of the data, ______ [e.g., data dictionary, metadata, documentation, statistical analysis plans, bench protocols, data collection instruments] will be created, shared, and associated with the relevant datasets.
DMPTool fill-in-the-blank prompt addendum: Add relevant parts of the following if working with clinical trials
In addition to ______ [individual participant data (IPD) dataset being shared by restricted access and/or aggregate data being shared openly], the researcher will share the ______ [describe any other elements of the final data package not already addressed]. Documentation and support materials will be compatible with the clinicaltrials.gov Protocol Registration Data Elements.
Sample answer by DMPTool
To facilitate the interpretation and reuse of the data, a README file and data dictionary will be generated and deposited into a repository along with all shared datasets. The README file will include method description, instrument settings, RRIDs of resources such as antibodies, model organisms, cell lines, plasmids, and other tools (e.g., software, databases, services), and Protocol DOIs issued from protocols.io. The data dictionary will define and describe all variables in the dataset.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12614, 945, 6199, 3536, 'State whether specialized tools, software, and/or code are needed to access or manipulate shared scientific data, and if so, provide the name(s) of the needed tool(s) and software and specify how they can be accessed.
', '', '
NIH Guidance
An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed, (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team) and, if known, whether such tools are likely to remain available for as long as the scientific data remain available.
Additional Guidance from DMPTool
Tool(s) and software should be identified, then plans should specify how the tools can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, available only from the research team). If custom code and scripts will be created, state how people can access those tools (e.g. deposit them in a GitHub repository and archive it via Zenodo to make them publicly available and citable).
In addition, file formats in which data are saved in a digital format can be divided into two general categories. It is recommended to use an open file format whenever possible for interoperability and long-term preservation. If proprietary file formats are used, look for ways to convert them to open file formats before sharing data in a repository.
DMPTool fill-in-the-blank prompt: If no specialized tools are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ [csv, txt, dicom, etc.] format and will not require the use of specialized tools to be accessed or manipulated.
DMPTool fill-in-the-blank prompt: If specialized tools (open source or proprietary) are needed to access or manipulate the data:
_____ [Data type - Imaging data, survey data, etc.] data will be made available in _____ format, which requires the use of specialized tools, such as _____ [include list of tools] to be accessed and manipulated.
These tools will be shared openly via ____.
OR
These tools are fee-based, proprietary software. Alternative access to the data will be provided by [describe the strategy for other sites to see or work with the data - potential strategies include committing to provide links to file viewers, or exporting files to a nonproprietary format for limited use and reuse].
Sample answer from DMPtool: Animal studies with computational modeling
The raw data generated via the confocal microscope is in the Carl Zeiss (.czi) file format. Zeiss software or Fiji ImageJ is required to access the raw data. The raw data generated via the Affymetrix Mouse Genome 430 2.0 Array is in the .CEL format. Statistical programs such as MATLAB or R can be used to analyze the raw data present in the CEL file.
Fiji ImageJ is open-source software that can be downloaded freely online. Links to this or other open-source viewers will be included with the documentation for the shared dataset. Matlab is available for purchase from Mathworks. R is a free software environment for statistical computing and graphics. RStudio is a free R development environment that runs on most operating systems. R Scripts produced through the course of the research will be made publicly available on the lab’s GitHub repository, and will be provided as Supplementary files for any publications through a Zenodo-GitHub link. Code will be available no later than when a publication has been submitted.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12615, 945, 6200, 3537, 'State what common data standards will be applied to the scientific data and associated metadata to enable interoperability of datasets and resources, and provide the name(s) of the data standards that will be applied and describe how these data standards will be applied to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist.
', '', 'NIH Guidance
An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). While many scientific fields have developed and adopted common data standards, others have not. In such cases, the Plan may indicate that no consensus data standards exist for the scientific data and metadata to be generated, preserved, and shared.
Additional Guidance from DMPTool
A standard specifies how exactly data and related materials should be stored, organized, and described. In the context of research data, the term typically refers to the use of specific and well-defined formats, schemas, vocabularies, and ontologies in the description and organization of data. However, for researchers within a community where more formal standards have not been well established, it can also be interpreted more broadly to refer to the adoption of the same (or similar) data management-related activities or strategies by different researchers and across different projects.
It is possible that your work will employ multiple formal standards or a mix of formal standards and other data management strategies. You should be as specific as possible when describing the standards used for each type of data included in your proposal.
', '
DMPTool fill-in-the-blank prompt
Data will be stored in common and open formats, such as ____ for our ____ data. Information needed to make use of this data [e.g., the meaning of variable names, codes, information about missing data, other metadata, etc.] along with references to the sources of those standardized names and metadata items will be included wherever applicable.
Addendum DMPTool fill-in-the-blank for if there are formal data standards for some/all of the data:
Whenever possible, we will use ______ [common data elements, standardized survey instruments, etc.] to structure and organize our data.
Our ____ data will be structured and described using the ____ standard, which has been widely adopted in the ____ community. [Add additional information about this standard, if applicable - e.g., implementation in data repositories, utility in combining/reusing datasets]
Addendum DMPTool fill-in-the-blank prompt for if there are no formal standards:
Formal standards for ____ data have not yet been widely adopted. However, our data and other materials will be structured and described according to best practices which are as follows: [list appropriate best practices].
Sample answer from DMPTool
In accordance with FAIR Principles for data, we will use open file formats (e.g. JPEG, MP4, CSV, TXT, PDF, HTML, etc.) and persistent unique identifiers (PIDs) such as RRIDs for resources (e.g., organisms, plasmids, antibodies, cell lines, software tools, and databases) and DOIs for protocols using protocols.io. The bioimaging community has not yet agreed on a single standard data format that is generated by all acquisition systems, but we will use OME-Files for data that will be preserved and shared.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12616, 945, 6201, 3538, '4A. Repository where scientific data and metadata will be archived: Provide the name of the repository(ies) where scientific data and metadata arising from the project will be archived.
', '', 'NIH Guidance
See Selecting a Data Repository on the NIH Scientific Data Sharing site.
NIH has provided additional information to assist in selecting suitable repositories for scientific data resulting from funded research: NOT-OD-21-016.
In brief, the first consideration (Option 1) goes to whether the FOA or Institute specifies a repository, in which case that repository must be used. The next priority (Option 2) goes to subject-specific repositories such as the Open Domain-Specific Data Sharing Repositories. If neither of those considerations fit, consider (Option 3) other potentially suitable options: PubMed Central attachments, NIH-supported generalist repositories, or your organization’s institutional repository.
NIH GDS Policy Considerations (for data subject to the GDS policy)
For human genomic data:
For Non-human genomic data:
Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.
', 'All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories]OR ________ [Add appropriate subject or disease repositories]
DMPTool fill-in-the-blank prompt
All dataset(s) that can be shared will be deposited in _________ [Add appropriate NIH-supported data repositories] OR ________ [Add appropriate discipline- or data-specific repository, generalist repository, or your institutional data repository]
Sample answer from DMPTool: Minimal information, imaging study
Imaging data will be deposited into NCI’s Imaging Data Commons. All other data described above in the “data to be shared” section will be deposited into Zenodo.
Sample answer from DMPTool: Minimal information, clinical study
Aggregate clinical trials data from all arms of the study will be available in clinicaltrials.gov, along with related metadata. All other data described above in the “data to be shared” section will be deposited into the National Addiction & HIV Data Archive Program (NAHDAP) repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12617, 945, 6201, 3539, '4B. How scientific data will be findable and identifiable: Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
', '', 'NIH Guidance
Using unique Persistent Identifiers (PIDs) enables data to be findable, identifiable, and accessible. Per NOT-OD-21-016, a requirement is that the repository assigns datasets a citable, unique persistent identifier, such as a digital object identifier (DOI) or accession number, to support data discovery, reporting, and research assessment. The identifier points to a persistent landing page that remains accessible even if the dataset is de-accessioned or no longer available.
', 'DMPTool fill-in-the-blank prompt
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available under a _______ [Insert license information]
OR
The _________ [repository name] provides metadata, persistent identifiers [insert whether DOI, handles, other], and long-term access. This repository is supported by ________[Insert funder/organization] and dataset(s) are available through a request process __________ [Insert information about request process].
Sample answer by DMPTool: Minimal information
[Repository Name] provides searchable study-level metadata for dataset discovery. [Repository] assigns DOIs as persistent identifiers, and has a robust preservation plan to ensure long-term access. Data will be discoverable online through standard web search of the study-level metadata as well as the persistent pointer from the DOI to the dataset.
Sample answer by DMPTool: Vivli clinical trials data repository
Vivli provides access to data and documentation through study-level metadata specific to clinical trials description, long-term preservation and access, and Vivli-issued DOIs. In addition to DOIs, Vivli records are cross-searchable by the clinicaltrials.gov registration ID. Access request processes are described in detail with each data record.
Sample answer by DMPTool: Expanded identifier discovery information
We will use Persistent Unique Identifiers (PIDs) to improve data findability across all dissemination outputs. PIDs used will include ORCID iDs for people, DOIs for outputs (e.g., datasets, protocols), Research Resource IDentifiers (RRIDs) for resources, and Research Organization Registry (ROR) IDs and funder IDs for places, as much as possible to make data identifiable and findable. We will also use indexed metadata, such as MeSH terms with a unique URL to make scientific data easily findable. We will keep our ORCID Records up to date with DOIs for our datasets and publications, ROR, and funder IDs to increase findability.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12618, 945, 6201, 3540, '4C. When and how long the scientific data will be made available: Describe when the scientific data will be made available to other users (i.e., no later than time of an associated publication or end of the performance period, whichever comes first) and for how long data will be available.
', '', 'NIH Guidance
NIH encourages scientific data be shared as soon as possible, and no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider relevant requirements and expectations (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available. NIH encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public. Identify any differences in timelines for different subsets of scientific data to be shared.
Genomic data has further guidance on release expectations and timelines.
', '
DMPTool fill-in-the-blank prompt
Shared data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of _____[duration] years after the end of the funding period.
Sample answer by DMPTool
All scientific data generated from this project will be made available as soon as possible, and no later than the time of publication or the end of the funding period, whichever comes first. The duration of preservation and sharing of the data will be a minimum of 10 years after the funding period.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12619, 945, 6202, 3541, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data: NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data. Describe and justify any applicable factors or data use limitations affecting subsequent access, distribution, or reuse of scientific data related to informed consent, privacy and confidentiality protections, and any other considerations that may limit the extent of data sharing.
', '', 'NIH Guidance
NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:
Whether access to scientific data derived from humans will be controlled (i.e., made available by a data repository only after approval).
NIH GDS Policy Considerations (for data subject to the GDS policy)
See the policy website and NOT-OD-22-198 for further expectations for sharing human genomic data subject to the GDS Policy.
Additional DMPTool Guidance
Some data may require extra preparation before they can be shared. This is the section to describe what legal, ethical, or technical issues will require limiting the sharing of your data. Examples may include existing legal limits such as data licenses or use agreements, issues of proprietary IP development, technical limits about the size or structure of the data, or ethical issues for human subjects privacy.
Key issues in justification of human subjects data may be informed consent (e.g., disease-specific limitations, particular communities’ concerns) or privacy and confidentiality protections (i.e., de-identification, Certificates of Confidentiality, and other protective measures). Specific steps for human subjects data preparation can be addressed in the protections for privacy subquestion below.
', 'DMPTool fill-in-the-blank prompt
There are no anticipated factors or limitations that will affect the access, distribution or reuse of the scientific data generated by the proposal.
OR
Due to _______ [ethical/legal/technical considerations], access/distribution/reuse of the resulting scientific data will be limited and approved/monitored by ________ [describe the approach to limiting access/distribution/reuse].
Sample answer by DMPTool for animal studies
To address safety and security concerns related to capturing and distributing pictures or video of vertebrate research animals, access and distribution of behavioral video files generated in our lab during brain inactivation studies of non-human primates will be limited as described and justified in the IACUC protocol governing the project and in compliance with the "Image Recordings of Research Animals" Standard Operating Procedure at our institution. There are no other factors that will impact access, distribution, and reuse for all other scientific data generated by this study.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12620, 945, 6202, 3542, '5B. Whether access to scientific data will be controlled: State whether access to the scientific data will be controlled (i.e., made available by a data repository only after approval).
', '', 'Additional DMPTool guidance
Check the repository you intend to use to find out more about whether and how the repository supports controlled access.
', 'Researchers who are not using controlled access repositories can skip this section or state:
Controlled access will not be used. The data that is shared will be shared by unrestricted download.
DMPTool fill-in-the-blank prompts for researchers selecting controlled access repositories
Given the sensitive nature of the dataset, data will be made available in ________ data repository, which restricts access to the data to ______ [describe restriction, e.g. to qualified investigators with an appropriate research question and approved data use agreement (DUA)]. Data can be accessed by _____ [describe data repository access methods and measures].
Sample answer from DMPTool for clinical trials data sharing in the Vivli repository
Data will be available by controlled access only. To access data arising from this project, users must complete the Vivli data request form and sign the Vivli Data Use Agreement (DUA), which limits subsequent use to the terms of the approved request and requires that users maintain data security, and refrain from any attempts to re-identify research participants or engage in any unauthorized uses of the data. To get access to the data, the user must submit a valid scientific question, include a statistical analysis plan, and complete all required fields on the Vivli data request form. Vivli will review the data request for completeness.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12621, 945, 6202, 3543, '5C. Protections for privacy, rights, and confidentiality of human research participants: if generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures).
', '', '
Additional DMPTool Guidance
Certain kinds of data, especially human subjects data, require extra preparation before they can be shared to ensure participant privacy. In this section, you will describe your approach to preparing human subjects data for sharing and note any additional restrictions or policies that will impact access to your data. If you are working with human subjects you should also describe how you will address data management and sharing in your informed consent process. You will also need to describe your methods for ensuring privacy and confidentiality, including how you will de-identify your data. If you have decided that a controlled access repository (where researchers must apply to access data) is a better fit for your data than an open repository, you should describe the repositorys access procedures. Finally, if there are any other laws, policies, or existing agreements that impact your ability to share your data, they should be described here.
Issues to consider:
This subsection applies to studies involving human research participants. Other studies can generally skip question 5.3
DMPTool fill-in-the-blank prompt for human subjects data
In order to ensure participant consent for data sharing, IRB paperwork and informed consent documents will include language describing plans for data management and sharing of data, describing the motivation for sharing, and explaining that personal identifying information will be removed.
To protect participant privacy and confidentiality, shared data will be de-identified using the ______ methods [describe de-identification method, noting any other applicable laws or policies such as HIPAA].
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (12622, 945, 6203, 3544, 'Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles, roles).
', '', '
Describe how and by whom compliance with this Plan will be managed. If oversight and roles will include the addition of study personnel for oversight of data management and sharing, describe reasonable, allowable personnel costs in the budget justification rather than the DMS Plan.
', 'DMPTool fill-in-the-blank prompt
Lead PI ____[name]___, ORCID: __[ORCID ID]___, will be responsible for the day-to-day oversight of lab/team data management activities and data sharing. Broader issues of DMS Plan compliance oversight and reporting will be handled by the PI and Co-I team as part of general [campus(es)] stewardship, reporting, and compliance processes.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); +INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (13044, 967, 6355, 3685, 'Add one row for each broad type of data to be generated and shared in the project. If data to be generated is not yet known or otherwise does not conform to the columns in this table, explain in the text box below. Be sure to describe any data that will be generated but not shared in Section II and provide a strong justification for why the data cannot be shared. Complete Section VII if generating any genomic data that is subject to the NIH Genomic Data Sharing (GDS) policy.
', '', 'If data to be generated is not yet known or otherwise does not conform to the columns in this table, delete the table and write in an explanation of extenuating circumstances instead.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder1_id, NOW(), @default_funder1_id, NOW()); -INSERT INTO versionedSectionTags (versionedSectionId, tagId, createdById, created, modifiedById, modified) VALUES (392, 9, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedSectionTags (versionedSectionId, tagId, createdById, created, modifiedById, modified) VALUES (393, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedSectionTags (versionedSectionId, tagId, createdById, created, modifiedById, modified) VALUES (394, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedSectionTags (versionedSectionId, tagId, createdById, created, modifiedById, modified) VALUES (396, 8, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); -INSERT INTO versionedSectionTags (versionedSectionId, tagId, createdById, created, modifiedById, modified) VALUES (856, 1, @default_funder1_id, CURDATE(), @default_funder1_id, CURDATE()); 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-INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (403, 94, 'Plans for archiving and preservation', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (404, 94, 'Data retention', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (611, 132, 'Types of data produced', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (612, 132, 'Data and metadata formats', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (613, 132, 'Roles and responsibilities', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (614, 132, 'Policies for access and sharing', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (615, 132, 'Policies for re-use and re-distribution', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (616, 132, 'Plans for archiving and preservation', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (617, 133, 'Roles and responsibilities', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (618, 133, 'Expected data', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (619, 133, 'Period of data retention', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (620, 133, 'Data format and dissemination', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (621, 133, 'Data storage and preservation of access', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (622, 133, 'Additional possible data management requirements', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (717, 161, 'Products of Research', ' ', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (718, 161, 'Data Formats and Standards', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (719, 161, 'Dissemination, Access and Sharing of Data', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (720, 161, 'Re-Use, Re-Distribution and Production of Derivatives', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (721, 161, 'Archiving of Data', ' ', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (809, 181, 'Products of the research', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (810, 181, 'Data format', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (811, 181, 'Access to data and data sharing practices and policies', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (812, 181, 'Policies for re-use, re-distribution and production of derivatives', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (813, 181, 'Archiving of data', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (814, 181, 'Software', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (823, 186, 'Types of data', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (824, 186, 'Data and metadata standards', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (825, 186, 'Policies for access, sharing, and privacy', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (826, 186, 'Policies for re-use, re-distribution, derivatives', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (827, 186, 'Plans for archiving and preservation', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (828, 186, 'Roles and responsibilities', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (850, 190, 'Products of the Research', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (851, 190, 'Data Format', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (852, 190, 'Access to Data and Data Sharing Practices and Policies', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (853, 190, 'Policies for Re-Use, Re-Distribution, and Production of Derivatives', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (854, 190, 'Archiving of Data', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (855, 191, 'Products of the Research', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (856, 191, 'Data Format', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (857, 191, 'Access to Data and Data Sharing Practices and Policies', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (858, 191, 'Policies for Re-Use, Re-Distribution, and Production of Derivatives', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (859, 191, 'Archiving of Data', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (860, 191, 'Cost of Implementing the DMP', '
', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1146, 248, 'Data and Materials Produced', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1147, 248, 'Standards, Formats and Metadata', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1148, 248, 'Roles and Responsibilities', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1149, 248, 'Dissemination Methods', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1150, 248, 'Policies for Data Sharing and Public Access', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1151, 248, 'Archiving, Storage and Preservation', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1497, 331, 'Data Policy Compliance', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1498, 331, 'Pre-Cruise Planning', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1499, 331, 'Description of Data Types', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1500, 331, 'Data and Metadata Formats and Standards', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1501, 331, 'Data Storage and Access During the Project', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1502, 331, 'Mechanisms and Policies for Access, Sharing, Re-Use, and Re-Distribution', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1503, 331, 'Plans for Archiving', '', '', '', 0, 7, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1504, 331, 'Roles and Responsibilities', '', '', '', 0, 8, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1518, 335, 'Data and sample types', '
Describe the types of data and samples expected to result from the proposed work.
', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1519, 335, 'Data/sample deposit, access, and preservation', 'Describe how each type of data or sample will be deposited, made accessible, and preserved
', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1520, 336, 'Types of data', '', '', '', 0, 1, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1521, 336, 'Data and metadata standards', '', '', '', 0, 2, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1522, 336, 'Policies for access and sharing', 'Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', '', 0, 3, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1523, 336, 'Policies and provisions for re-use, re-distribution', '', '', '', 0, 4, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1524, 336, 'Plans for archiving and preservation of access', '', '', '', 0, 5, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1662, 362, 'Element 1: Data Types', '', '', '', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1663, 362, 'Element 2: Related Tools, Software/Code, and/or Other Digital Products', '', '', '', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1664, 362, 'Element 3: Data Standards for Interoperability', '', '', '', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1665, 362, 'Element 4: Data Preservation, Access, Reuse, and Associated Timelines', '', '', '', 0, 4, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1666, 362, 'Element 5: Factors Affecting Access, Distribution, or Reuse', '', '', '', 0, 5, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1667, 362, 'Element 6: Review and Updating of the Data Management and Sharing Plan:', '', '', '', 0, 6, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1668, 364, 'Products of Research', '', '', '', 0, 1, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1669, 364, 'Data Format Standards', '', '', '', 0, 2, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1670, 364, 'Access and sharing', '', '', '', 0, 3, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1671, 364, 'Policies and provisions for re-use, re-distribution, and production of derivatives', '', '', '', 0, 4, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1672, 364, 'Archiving of Data, Samples, and Other Relevant Research Products', '', '', '', 0, 5, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1, 1, 'Products of Research', '', '', '', 0, 1, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2, 1, 'Data Storage and Preservation', '', '', '', 0, 2, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3, 1, 'Data Formats and Metadata', '', '', '', 0, 3, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (4, 1, 'Data Dissemination & Policies for Data Sharing and Public Access', '', '', '', 0, 4, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (5, 1, 'Roles and Responsibilities', '', '', '', 0, 5, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (17, 3, 'Types of data produced', '', '', '', 0, 1, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (18, 3, 'Data and metadata formats', '', '', '', 0, 2, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (19, 3, 'Access polices and provision', '', '', '', 0, 3, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (20, 3, 'Means of sharing the outcome', '', '', '', 0, 4, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (34, 6, 'Data Collected, Formats and Standards', '', '', '', 0, 1, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (35, 6, 'Data Storage and Preservation', '', '', '', 0, 2, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (36, 6, 'Dissemination Methods', '', '', '', 0, 3, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (37, 6, 'Policies for Data Sharing and Public Access', '', '', '', 0, 4, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (38, 6, 'Roles and Responsibilities', '', '', '', 0, 5, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (367, 90, 'Publication', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (368, 90, 'Data types and privacy', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (369, 90, 'Access', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (370, 90, 'Re-use, re-distribution, derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (371, 90, 'Archiving and preservation', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (372, 90, 'Data dissemination and sharing', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (386, 92, 'Types of data produced', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (387, 92, 'Data and metadata standards', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (388, 92, 'Policies for access and sharing', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (389, 92, 'Policies for re-use, re-distribution, derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (390, 92, 'Plans for archiving and preservation', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (391, 93, 'Roles and responsibilities', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (392, 93, 'Types of data or products', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (393, 93, 'Data storage, preservation, and sharing', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (394, 93, 'Restrictions on data or product storage, access, preservation, or sharing', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (395, 93, 'Data formats', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (396, 93, 'Period of data retention', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (397, 93, 'Third-party preservation', '', '', '', 0, 7, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (398, 93, 'Additional possible data management requirements', '', '', '', 0, 8, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (399, 94, 'Publication', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (400, 94, 'Data types and privacy', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (401, 94, 'Access and sharing', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (402, 94, 'Policies and provisions for re-use, re-distribution, derivates', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (403, 94, 'Plans for archiving and preservation', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (404, 94, 'Data retention', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (611, 132, 'Types of data produced', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (612, 132, 'Data and metadata formats', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (613, 132, 'Roles and responsibilities', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (614, 132, 'Policies for access and sharing', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (615, 132, 'Policies for re-use and re-distribution', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (616, 132, 'Plans for archiving and preservation', 'The guidance below is provided by the NSF Arctic Data Center to assist you with creating a data management plan that meets requirements and facilitates the use of data center resources.', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (617, 133, 'Roles and responsibilities', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (618, 133, 'Expected data', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (619, 133, 'Period of data retention', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (620, 133, 'Data format and dissemination', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (621, 133, 'Data storage and preservation of access', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (622, 133, 'Additional possible data management requirements', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (717, 161, 'Products of Research', ' ', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (718, 161, 'Data Formats and Standards', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (719, 161, 'Dissemination, Access and Sharing of Data', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (720, 161, 'Re-Use, Re-Distribution and Production of Derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (721, 161, 'Archiving of Data', ' ', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (809, 181, 'Products of the research', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (810, 181, 'Data format', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (811, 181, 'Access to data and data sharing practices and policies', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (812, 181, 'Policies for re-use, re-distribution and production of derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (813, 181, 'Archiving of data', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (814, 181, 'Software', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (823, 186, 'Types of data', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (824, 186, 'Data and metadata standards', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (825, 186, 'Policies for access, sharing, and privacy', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (826, 186, 'Policies for re-use, re-distribution, derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (827, 186, 'Plans for archiving and preservation', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (828, 186, 'Roles and responsibilities', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (850, 190, 'Products of the Research', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (851, 190, 'Data Format', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (852, 190, 'Access to Data and Data Sharing Practices and Policies', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (853, 190, 'Policies for Re-Use, Re-Distribution, and Production of Derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (854, 190, 'Archiving of Data', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (855, 191, 'Products of the Research', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (856, 191, 'Data Format', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (857, 191, 'Access to Data and Data Sharing Practices and Policies', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (858, 191, 'Policies for Re-Use, Re-Distribution, and Production of Derivatives', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (859, 191, 'Archiving of Data', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (860, 191, 'Cost of Implementing the DMP', '
', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1146, 248, 'Data and Materials Produced', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1147, 248, 'Standards, Formats and Metadata', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1148, 248, 'Roles and Responsibilities', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1149, 248, 'Dissemination Methods', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1150, 248, 'Policies for Data Sharing and Public Access', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1151, 248, 'Archiving, Storage and Preservation', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1497, 331, 'Data Policy Compliance', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1498, 331, 'Pre-Cruise Planning', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1499, 331, 'Description of Data Types', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1500, 331, 'Data and Metadata Formats and Standards', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1501, 331, 'Data Storage and Access During the Project', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1502, 331, 'Mechanisms and Policies for Access, Sharing, Re-Use, and Re-Distribution', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1503, 331, 'Plans for Archiving', '', '', '', 0, 7, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1504, 331, 'Roles and Responsibilities', '', '', '', 0, 8, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1518, 335, 'Data and sample types', '
Describe the types of data and samples expected to result from the proposed work.
', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1519, 335, 'Data/sample deposit, access, and preservation', 'Describe how each type of data or sample will be deposited, made accessible, and preserved
', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1520, 336, 'Types of data', '', '', '', 0, 1, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1521, 336, 'Data and metadata standards', '', '', '', 0, 2, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1522, 336, 'Policies for access and sharing', 'Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', '', 0, 3, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1523, 336, 'Policies and provisions for re-use, re-distribution', '', '', '', 0, 4, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1524, 336, 'Plans for archiving and preservation of access', '', '', '', 0, 5, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1662, 362, 'Element 1: Data Types', '', '', '', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1663, 362, 'Element 2: Related Tools, Software/Code, and/or Other Digital Products', '', '', '', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1664, 362, 'Element 3: Data Standards for Interoperability', '', '', '', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1665, 362, 'Element 4: Data Preservation, Access, Reuse, and Associated Timelines', '', '', '', 0, 4, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1666, 362, 'Element 5: Factors Affecting Access, Distribution, or Reuse', '', '', '', 0, 5, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1667, 362, 'Element 6: Review and Updating of the Data Management and Sharing Plan:', '', '', '', 0, 6, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1668, 364, 'Products of Research', '', '', '', 0, 1, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1669, 364, 'Data Format Standards', '', '', '', 0, 2, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1670, 364, 'Access and sharing', '', '', '', 0, 3, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1671, 364, 'Policies and provisions for re-use, re-distribution, and production of derivatives', '', '', '', 0, 4, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO sections (id, templateId, name, introduction, requirements, guidance, bestPractice, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1672, 364, 'Archiving of Data, Samples, and Other Relevant Research Products', '', '', '', 0, 5, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (1, 1, 1, 'What kind of data will be collected, standards employed, and for how long will data be retained?
', '', '
DataONE Best Practice: Define Expected Data Outcomes and Types
What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data?
', '', '
re3data: Registry of data repositories
DataONE Best Practice: Document and Store Data Using Stable File Formats
Describe standards to be used for data and metadata format and content.
', '', '
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Suitable Repositories for your Data
What will be the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)?
', '', '
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Data Sensitivity
What are the rights and obligations of all parties with respect to their roles in and responsibilities for the management and retention of research data (including contingency plans for the departure of key personnel from the project)?
', '', '
DataONE Best Practice: Identify Suitable Repositories for your Data
DataONE Best Practice: Revisit Data Management Plan Throughout the Project Life Cycle
Types of data to be produced
', '', '
NSF Emerging Frontiers in Research and Innovation (EFRI)
NSF Emerging Frontiers in Research and Innovation Program Solicitation
Guidance
Standards that would be applied for data format and metadata content
', '', '
NSF Emerging Frontiers in Research and Innovation (EFRI)
NSF Emerging Frontiers in Research and Innovation Program Solicitation
Guidance
Access polices and provision
', '', 'Access policies:
Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. If the data is of a sensitive nature—human subject concerns, potential patentability, species/ecological endangerment concerns—that public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements; anonymiztion of data; restricted access, only available within a secure network). Consider these questions:
Sharing the research with the rest of the scientific community
', '', 'Means of sharing:
The description should be specific and describe what, how, and when the community would have access to the outcome of the project. Will data be accessible on a web page, through publications, databases, via open-access repository, etc.? If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). Consider these questions:
Describe the data that will be collected, and the data and metadata formats and standards used.
', '', 'Data collected:
Describe the data to be collected (actual observations) during your research including amount (if known). Name the type of data, the instrument or collection approach, and how the data will be sampled. If actual data are interpreted, note the interpretation. Describe any quality control measures. Also describe the final derivative products (datasets and software or computer code) and the analysis used including analytical software packages that are required for replication, etc. Describe the format of your data; think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available. For example, for most ecological data, documentation should be structured in Ecological Metadata Language (EML). An example of metadata could also be as simple as a "readme file" to explain variables, structure of the files, etc. Consider these questions:
Describe what physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends.
', '', 'Data storage and preservation:
The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
Describe what media and dissemination methods will be used to make the data and metadata available to others after the grant ends.
', '', 'Dissemination methods:
Describe how and where you will make these data and metadata available to the community. Remember BIO is committed to timely and rapid data distribution; make sure you address how soon your data will be available. Indicate what data will be made available and preserved. Will data be accessible on a web page, by email request, via open-access repository, etc.? Consider these questions:
Describe the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)
', '', 'Policies for sharing:
Describe the policies under which these data will be made available. It is very important, the reason a DMP is required, that you specify how you will share your data with non-group members after the project is completed. If the data is of a sensitive nature—privacy or ecological endangerment concerns, for instance—and public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements, anonymized data, only available within a secure network, etc.). Consider these questions:
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project) after the grant ends.
', '', 'Roles and responsibilities:
Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself.
', '', 'Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer.
', '', 'Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable.
', '', 'NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers.
', '', 'NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like.
', '', 'Each NSF grant contains, as part of the grant terms, an article implementing dissemination and sharing of research results.
', '', '
The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', 'The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', 'Specify the roles and responsibilities of all parties with respect to the DMP activities.
', '', 'Specify the types of data or products that will be generated (e.g., test scores, survey responses, images, data tables, video or audio data, sftware, curricular or exhibit materials).
', '', 'Specify how data or products are to be stored, preserved, and shared.
', '', 'Specify any restrictions on data or product storage, access, preservation, or sharing
', '', 'Specify what data formats will be used (e.g., XML files, websites, image files, data tables, software code, text documents, physical materials).
', '', 'Specify how long access to data and products, and sharing of data or products, will be maintained after the life of the project, and how any associated costs will be covered and by whom.
', '', 'If data or products are to be preserved by a third party, please refer to their preservation plans if available.
', '', 'More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself.
', '', 'Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer.
', '', '
Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable.
', '', '
NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers.
', '', 'NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like.
', '', '
Physics Division PIs should include in their Data Management Plan those aspects of data retention and sharing that would allow them to respond to a question about a published result. Members of formal collaborations may refer to the collaborations existing policies and practices.
', '', '
What types of data, samples, collections, software, materials, etc. will be produced during your project?
This is the most detailed section of the data management plan. Describe the categories of data being collected and how they tie into the data associated with the methods used to collect that data. Expect this section to be the most detailed section, taking up a large portion of your data management plan document.
', 'During this project, soil cores will be collected from three sites representing varying degrees of snow accumulation. Temperature, moisture and active layer thaw depth will be collected to record soil physical properties. Soil samples from each core will be analyzed for carbon concentration, nitrogen concentration and pH.
Aerial photos of each of the three sites will also be taken twice annually to visualize the snow cover. Additional data products that will be made available include data analysis codes in R and high school-level educational materials regarding soil properties in changing climatic conditions in the Arctic.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (959, 132, 611, 'What will be the approximate number and size of data files that will be produced during your project?
', '', 'This section is driven by sampling design, and is based on what you predict you will be collecting. Realistic estimates are sufficient. This section is important because reviewers need to understand what data you plan on collecting and how you plan on managing that data. ', 'In this project, there will be six experimental treatments applied to the Saxifraga cespitosa plants, with four replicates for each treatment collected three times during the year. Therefore, there will be approximately 72 data files each year (6 treatments x 4 replicates x 3 collections per year). The 72 data files will be approximately 720 MB in size.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (960, 132, 611, 'What type of metadata (information others might need to use your data) will be collected during your project?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
', '', 'Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.
The project will collect and record a description of the time of soil core collection in the field, along with the time of soil core processing in the laboratory. The exact locations and conditions of the field sites will be described as well as the laboratory conditions and location of soil sample analysis. A detailed description of the soil core sample collection and processing methods in the field, as well as the laboratory soil carbon and nitrogen concentration collection and processing methods will be included. Units will be recorded for all samples. Soil carbon and nitrogen will be reported in %C and %N, respectively, along with the C:N ratio and the %delta 13C and %delta 15N. Soil depth will be recorded in centimeters.
Quality control procedures will be followed in both the field and the laboratory during sample collection and processing, and the details of these procedures will be included. The decisions for the inclusion of each component of the project, including the specific sampling methods, units, and procedures, will be provided. The hardware and software used will be provided. R Studio will be used for coding and data analysis, with the code shared in a Github repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (961, 132, 612, '
What format(s) will data and metadata be collected, processed, and stored in?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
', '', 'Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. Additionally, please provide ORCiD identification for all individuals collecting and analyzing the data for proper citation and credit.
', '
The local and traditional knowledge data will be collected during interviews using tape recording devices. The survey answers will then be transcribed and exported to CSV files for storage. Metadata will be documented in CSV files. The soil core data will be collected by hand in the field and then entered into a CSV file for storage. The soil core metadata will be entered in CSV files along with the metadata. Imagery metadata from the core sites will be encoded in NetCDF files. All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (962, 132, 613, '
1. What parties and individuals will be involved with data management in this project?
2. What will be the roles and responsibilities of each party and or individual with respect to management of the data?
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
', '', 'Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. The purpose of this section is to ensure that the individuals ultimately responsible for ensuring compliance with the data management plan are both aware and agree to their roles.
', 'The project’s principal investigator, Jane Doe, will ultimately be responsible for all of the data management. It is Doe’s responsibility to make sure all of the project team members are taught the proper data management skills and uphold the data management requirements. Doe will delegate data management duties to the laboratory project data manager, Bonnie, along with graduate student, Clyde, working in the field. The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (964, 132, 614, '
How will data be accessed and shared during the course of the project?
Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publicly accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.
NSF Office of Polar Programs Guidelines
', 'During the course of the project, data files will be stored in a laboratory Github repository. The data will initially be stored in Excel files and transferred to CSV files. At the end of each year of data collection, the data files will deposited to a shared file system on the Github repository where all team members can access the files. ', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (963, 132, 614, 'Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research.
', '', '', 'Survey data taken during interviews with the local residents are expected to need provisions for confidentiality due to ethical restrictions and the protection of indigenous knowledge. This sensitive data is governed by an Institutional Review Board policy. Additionally, this project deals with endangered species, so similarly sensitive data, particularly location data, will also be exempted from the archiving requirements set for Arctic Sciences research due to confidentiality and species protection.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (965, 132, 614, '
When is the approximate release date of the data products?
Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
', '', 'NSF Office of Polar Programs Guidelines
', 'The data will be released within two years of data collection.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (966, 132, 615, '
How do you anticipate the data for this project will be used? Consider the following:
The salmon catch data are expected to be used by other researchers studying Arctic food web systems in addition to government agencies with regard to establishing catch limits in the area. Local fishermen and fish modellers may also make use of this data. The data will be added to a long-term data set to continue to observe changes in the region through time.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (967, 132, 615, 'Will any permission restrictions need to be placed on the data? Consider the following:
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data.
', 'All data will be accessible to the public and subject to usage and dissemination restrictions under the CC-0 Public Domain Dedication License.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (968, 132, 616, '
What is the long-term strategy for maintaining, curating, and archiving the data?
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:
The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (969, 133, 617, 'The DMP should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It should also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution or project. Any costs should be explained in the Budget Justification pages.
', '', 'The DMP should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained.
', '', 'SBE is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their DMP statement.
', '', 'The DMP should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders.
', '', 'The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories.
', '', 'More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'What types of data (experimental, computational, or text-based), metadata, samples, physical collections, models, software, curriculum materials, and other materials will be collected and/or generated in the course of the project? The DMP should describe the expected types of data to be retained, managed, and shared, and the plans for doing so. What descriptions of the metadata are needed to make the actual data products useful and reproducible for the general researcher? For collaborative proposals, the DMP should describe the roles and responsibilities of all parties with respect to the management of data (including contingency plans for the departure of key personnel from the project) both during and after the grant cycle.
', '', 'In what format and/or media will the data or products be stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats)? Where data are stored in unusual or not generally accessible formats, how may the data be converted to more accessible formats or otherwise made available to interested parties? When existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies. In general, solutions and remedies to providing data in an accessible format should be offered with minimal added cost.
', '', 'What specific dissemination approaches will be used to make data available and accessible to others, including any pertinent metadata needed to interpret the data? In this case, "available and accessible" refers to data that can be found and obtained without a personal request to the PI, for example by download from a public repository. What plans, if any, are in place for providing access to data, including websites maintained by the research group and contributions to public databases/repositories? For software or code developed as part of the project, include a description of how users can access the code (e.g., licensing, open source) and specific details of the hosting, distribution and dissemination plans. If maintenance of a website or database is the direct responsibility of the research group, what is the period of time the website or database is expected to be maintained? What are the practices or policies regarding the release of POST-AWARD MANAGEMENT data – for example, are they available before or after formal publication? What is the approximate duration of time that the data will be kept private? “Data sharing” refers to the release of data in response to a specific request from an interested party. What are the policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements? Research centers and major partnerships with industry or other user communities should also address how data are to be shared and managed with partners, center members, and other major stakeholders; publication delay policies (if applicable) should be clearly stated.
', '', 'What are your policies regarding the use of data provided via general access or sharing? For data to be deemed “re-usable,” it must be accompanied by any metadata needed to reproduce the data, e.g., the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other pertinent metadata. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should also be clearly articulated. For example, if you plan to provide data and images on your website, will the website contain disclaimers or condition regarding the use of the data in other publications or products?
', '', 'When and how will data be archived and how will access be preserved over time? For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). Where no data or sample repository exists for collected data or samples, metadata should be prepared and made publicly available over the Internet and the PI should employ alternative strategies for complying with the general philosophy of sharing research products and data as described above
', '', 'Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, HD5, Virtual Observatory-compliant tables, XML files, etc.). Include a description of any metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided.
', '', '"Access to data" refers to data made accessible to an interested party without the need for an explicit request from the interested party. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and contributions of your data to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period you plan to maintain the web site or data base. Note that data taken at national or private observatories may already be accessible through a public archive (perhaps after a standard proprietary period). Various forms of data (e.g. FITS images and tables, HD5 or other data tables) also may be deposited with published articles in the AAS journals and other journals. Attention should be paid to making accessible data sets that are products of well-defined surveys. Also describe your practice or policies regarding the release of data, for example whether data are posted before or after formal publication.
"Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. It is preferred that all data products be made available without requiring a special request to investigators.
', '', 'Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website?
', '', 'Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Special attention should be taken to selecting institutional sites that are expected to have a reasonably long lifetime.
', '', 'The Data Management Plan should describe the types of data, metadata, scripts used to generate the data or metadata, experimental results, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project.
', '', 'The Data Management Plan should address the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It should also cover any other types of information that would be maintained and shared regarding data, e.g. the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other metadata.
', '', 'The Data Management Plan should address the policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. It should cover any factors that limit the ability to manage and share data, e.g. legal and ethical restrictions on access to human subject data.
', '', 'The Data Management Plan should address the policies and provision for re-use, re-distribution, and the production of derivatives.
', '', 'The Data Management Plan should address the plans for archiving data, samples, and other research products, and for the preservation of access to them. It should cover the period of time the data will be retained and shared; how data are to be managed, maintained, and disseminated; and mechanisms and formats for storing data and making them accessible to others, which may include third party facilities and repositories.
', '', 'The Data Management Plan should clearly articulate how the PI and co-PIs plan to manage and disseminate data generated by the project. The plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data, and consider changes that would occur should a PI or co-PI leave the institution or project. It should describe how the research team plans to deposit data into any relevant and appropriate disciplinary repositories that are appropriately managed and that are likely to maintain the metadata necessary for future use and discovery. Any costs associated with implementing the DMP should be explained in the Budget Justification.
', '', 'The following questions are intended to assist PIs and panel members to prepare Data Management Plans and to evaluate them during merit review, respectively. The questions are sequential, that is, if (1) applies, then the remaining questions are irrelevant unless (2) also applies or the PI chooses to deposit the data or software in multiple repositories. The more detailed questions, (4)-(6), apply if (1) and (2) do not.
Describe the types of data (including metadata and annotations, primary or analyzed) and products that will be generated by the research, for example description of samples, numerical data on chemical systems such as spectra, chemical and physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, experimental protocols, algorith specifications, database schemas and data tables, data produced by simulations and software. Data and products generated from Broader Impact activities, such as educational materials, participant information, tutorials and other web-based materials, as well as assessment results, should also be included in the DMP.
', '', 'Describe the format and media in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally-accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies to providing data in an accessible format should be provided with minimal added cost.
', '', '"Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases or software repositories (e.g., NMRShiftDB, the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database and Github). For software or code developed as part of the project, include a description of how users can access the code (e.g. licensing, open source) and specific details of the hosting, distribution and dissemination plans. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Note as well any anticipated inclusion of your data in databases that mine the published literature (e.g. PubChem, NIST Chemistry WebBook). Consider using the Digital Object Identifiers (DOI) assignment mechanism not just for journal articles, but for suitably-archived, publishable data sets.
"Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. Discussion on the compliance with the NSFs Public Access Policy is also encouraged.
', '', 'Describe your policies regarding the use of data provided via general access or sharing. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should be defined. For example, if you plan to provide data and images on your website, will the website contain disclaimers or conditions regarding the use of the data in other publications or products?
', '', 'Describe when the data should be archived, how data will be archived, and how preservation of access will be handled. Are there provisions for data backup? Will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? What are the physical and cyber resources and facilities that will be used for data preservation and storage? Will there be an easily accessible index that douments where all archived data are stored and how they can be accessed? What are the roles and responsibilities of all parties with respect to the management and archiving of the data after the grant ends? How long will the data be maintained after the grant ends?
CHE-supported large research centers or other programs may specify more stringent data storage, sharing and archiving procedures for research conducted under their awards. Such requirements will be specified in the program solicitation and award conditions.
', '', 'Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, existence of metadata, etc).
', '', 'Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases, and the mechanism for making the existence of an archive publicly known (e.g. by indicating the data sharing mechanism in publications that recognize NSF support). If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data – for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements.
', '', 'Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website?
', '', 'Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available).
', '', 'If implementing the DMP will incur additional costs to the project this fact should be mentioned in the appropriate section of the plan (for example the cost of setting up and maintaining a web site). Details of the costs must be included in the budget justification in the budget section of the proposal.
', '', 'Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.)
', '', '
Describe the standards to be used for all the data types anticipated, including data or file format and metadata. [Note: Where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies.]
', '', '
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project).
', '', '
Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends.
', '', '
Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights.
', '', '
Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education. Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?)
', '', '
Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES).
', '', 'NSF Division of Ocean Sciences Sample and Data Policy
NSF Frequently Asked Questions (FAQs) for Public Access
NSF Guidance on Data Management Plans
NSF GEO Directorate Data Policies
', 'The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2921, 331, 1498, 'If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions:
If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO along with dataset metadata.
Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available).
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2922, 331, 1499, 'Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them.
', '', 'It may be useful to group data into four categories:
Keep in mind that code or software developed through your project must also be made publicly available in compliance with NSF Policies. Code may be contributed to BCO-DMO or published with a DOI through Zenodo.
If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determined at a later date.
The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).
Observational Datasets:
Experimental Datasets:
Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions:
Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses. Whenever possible, quality flags should be included as columns within each dataset. The use of standard vocabularies/naming conventions is highly recommended.
Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2924, 331, 1501, 'Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following:
BCO-DMO “How-To” Pages
NSF Division of Ocean Sciences Sample and Data Policy
NSF Frequently Asked Questions (FAQs) for Public Access
', '
The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2925, 331, 1502, 'Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following:
Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.
Data Sharing via BCO-DMO
If the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.
Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.
BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.
Refer to the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.
Genomic Data and Other Specialized Repositories
Provisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.
BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.
Underway Shipboard Data
All routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.
Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers and related metadata will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO online Submission Tool. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publicly available without restriction once submitted to the public repositories.
Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use).
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2926, 331, 1503, 'Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following:
R2R will ensure that the original underway measurements are archived permanently at NCEI and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2927, 331, 1504, 'Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following:
', '
Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2971, 335, 1518, 'List the types of data and samples to be collected and/or generated. The listing of each data/sample type should briefly identify what metadata will be provided and when data/sample preparation will be considered complete. (Definitions of “data” and “samples” are explained above within “EAR requirements.”) For proposals providing community-serving infrastructure or research services, the DMP should describe the data/sample types to be managed and what guidance or support will be provided to help users meet their data/sample sharing obligations. EAR recognizes that data/samples may undergo multiple transformations in the research process (including destructive analyses), and disciplinary expectations for assignment of metadata and retention of intermediate data and sample products may vary.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2972, 335, 1518, 'For each data or sample type, identify which personnel and institution(s) will be designated for its management, including contingency plans for the departure of key personnel from the project. For collaborative projects, PI(s) of the award(s) associated with the designated personnel and institution(s) are ultimately responsible for overseeing and reporting on their data and sample management activities.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2973, 335, 1519, 'For each data type listed, identify an appropriate long-lived FAIR-aligned repository for data deposit, the timeframe for public data access, and the expected period of data preservation. For each sample type listed, identify an appropriate long-lived FAIRaligned repository for indexing sample metadata, the location for sample storage (preferably a repository appropriate for the specific sample type), and the expected period of sample preservation. (Required timeframes for data/sample access are specified above within “EAR Requirements.”) Many repositories commit to preserve access to data/samples indefinitely; any deviations from this expectation should be explained. PIs are encouraged to coordinate with designated repositories in advance of planned data/sample submission.
', '', 'NSF EAR Guidance:
All new data resulting from the project must be made publicly accessible within two (2) years after completion of data collection or generation, via appropriate long-lived FAIRaligned repositories. Expected timelines for data collection or generation may vary by data type and should align with appropriate disciplinary expectations. All new data collected via continuing observations, large-scale community projects, or RAPID awards must be made accessible as close to the time of initial collection as is practicable. All data in support of peer-reviewed scholarly publications resulting from the project must also be made publicly accessible at or before the time of publication. Exceptions to this policy must be justified (e.g., if an appropriate repository does not exist, or if data access must be restricted). “Data available upon request” is not acceptable.
Metadata describing all new samples resulting from the project must be publicly indexed within two (2) years after sample collection is considered complete, via appropriate long-lived FAIR-aligned repositories. Metadata describing samples collected via continuing observations, large-scale community projects, or RAPID awards must be indexed and made accessible as close to the time of collection as is practicable. All sample metadata in support of peer-reviewed scholarly publications must also be publicly indexed at or before the time of publication. Publicly indexed sample metadata should specify provisions for sample access, including the expected period and location of sample preservation, preferably via a repository appropriate for the specific sample type. The samples themselves should also be made publicly accessible within the above timeframes; situations in which samples cannot be made publicly accessible should be explained.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2974, 335, 1519, 'In most cases, it is sufficient for the DMP to identify the repository(ies) to be used and the timeframe for access and preservation for each type of data/sample identified. In these cases, the selected repository(ies) should align with FAIR principles and community-specific standards. Occasionally, appropriate long-lived FAIR-aligned repositories do not exist for certain types of data or samples. In such cases, it may be necessary to adopt alternative approaches to data access and retention, such as via use of a local computer server. In such cases, the DMP should explain how the proposed approach fulfills important attributes for FAIR-aligned repositories, consistent with OSTP guidance on “Desirable Characteristics of Data Repositories for Federally Funded Research.”9 These attributes include, but are not limited to, the following:
• Findability. Data should be findable via standard search tools, such as through the assignment of globally unique persistent identifiers (e.g., Digital Object Identifiers (DOIs) and International Geo Sample Numbers (IGSNs)) and rich metadata that is indexed in a searchable resource.
• Accessibility. Data should be publicly accessible to other researchers, at no more than incremental cost, within the specified timeframe. Any data access limitations must be justified. “Data available upon request” is not acceptable.
• Interoperability. To ensure interoperability, data should be described via appropriate metadata standards, in alignment with expectations of the associated scientific discipline(s).
• Reusability. To facilitate the broadest possible data reuse, data should be assigned clear and accessible usage licenses and metadata descriptors that identify provenance. EAR expects the adoption of unrestrictive open licenses except with specific justification.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2975, 336, 1520, 'The Division of Earth Sciences requires that full data sets, derived data products (e.g. model results, output, and workflows), software, and physical collections must be made publicly accessible within two (2) years of final collection.
', '', 'Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures.
', '', 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', '1A. Types and amount of scientific data expected to be generated in the project:
Summarize the types and estimated amount of scientific data expected to be generated in the project.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3347, 362, 1662, '1B. Of the generated scientific data in 1.A, the scientific data that will be preserved and shared, and the associated rationale:
Describe which types of scientific data from the project will be preserved and shared and briefly provide the rationale for this decision.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3348, 362, 1662, '1C. Metadata and associated documentation:
Briefly list the metadata (provides information about the scientific data) and any associated documentation (e.g., study protocols, research methods, and data-collection instruments) that will be made accessible to facilitate interpretation of the preserved and shared scientific data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3349, 362, 1663, '2A. Specialized tools, Software/Code, and/or Services for Access or Interpretation
State whether specialized tools, software/code and/or services are needed to access, manipulate, or interpret the preserved and shared data, and if so, provide the name(s) of the tool(s) and software/code or services, and specify how they can be found, accessed, and used (a link may be adequate).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3350, 362, 1663, '2B. Software/Code and/or Other Digital Products Produced:
State software/code and/or other digital products expected to result from the successful execution of the project and to be distributed according to FAIR principles. Include any license intended to be used for the release and a justification for the choice, and how the product will be made accessible (include methods used to advertise to the broader community). Machine learning models should ideally be distributed along with associated training data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3351, 362, 1664, '3. State what common data standards will be applied to the preserved and shared scientific data, and associated metadata to enable interoperability of datasets and resources and describe how these data standards will be applied. If applicable, indicate that no consensus standards exist.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3352, 362, 1665, '4A. Repository where scientific data and metadata will be available for reuse:
Provide the name of the repository(ies) from which preserved and shared scientific data and metadata arising from the project will be available for reuse; see Dear Colleague Letter: Effective Practices for Making Research Data Discoverable and Citable (Data Sharing) and Desirable Characteristics of Data Repositories for Federally Funded Research.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3353, 362, 1665, '4B. How scientific data will be findable and identifiable:
Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier (e.g., DOI), listing in a registry, or other standard indexing techniques.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3354, 362, 1665, '4C. When and for how long the scientific data will be made broadly available:
Describe when the scientific data will be made broadly available (i.e., no later than when an associated publication appears or end of the performance period, whichever comes first) and for how long data will be available. Include any external factors that may affect time of appearance.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3355, 362, 1666, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data:
NSF expects that in drafting Plans, researchers should maximize the appropriate sharing of scientific data. Describe and clearly justify any applicable factors or data-use limitations affecting subsequent access, distribution, or reuse of scientific data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3356, 362, 1666, '5B. Protections for privacy, rights, and confidentiality of human research participants:
If generating data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures). You should include in Element 5A above factors related to informed consent, privacy and confidentiality protections that may limit access, distribution, or reuse of such data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3357, 362, 1667, '6. The Data Management and sharing Plan should be a living document that is updated during the lifetime of the award, as needed. Describe how and when this Plan will be reviewed, re-evaluated, and updated, to ensure it best serves its purpose. For example, updates to the Plan can be reported in Annual Project Reports.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3358, 364, 1668, 'Describe the types of data and products to be produced during the project. Examples of data and products include: materials samples; characterization data; (meta)data that provides information on the data, e.g. synthesis conditions or community codes used; simulation data; and software. Data and other products generated from Broader Impact activities, such as education materials and assessment results, should also be included in the plan, together with Institutional Review Board (IRB) considerations and clearance, if applicable. This inventory should inform the scope of the Data Management Plan and the requirements to preserve, curate, and share the products that result from the project.', '', 'Describe your policies regarding the use of data provided via general access or sharing, or specific licensing provisions, if applicable. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data.
', '', 'What kind of data will be collected, standards employed, and for how long will data be retained?
', '', '
DataONE Best Practice: Define Expected Data Outcomes and Types
What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data?
', '', '
re3data: Registry of data repositories
DataONE Best Practice: Document and Store Data Using Stable File Formats
Describe standards to be used for data and metadata format and content.
', '', '
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Suitable Repositories for your Data
What will be the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)?
', '', '
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Data Sensitivity
What are the rights and obligations of all parties with respect to their roles in and responsibilities for the management and retention of research data (including contingency plans for the departure of key personnel from the project)?
', '', '
DataONE Best Practice: Identify Suitable Repositories for your Data
DataONE Best Practice: Revisit Data Management Plan Throughout the Project Life Cycle
Types of data to be produced
', '', '
NSF Emerging Frontiers in Research and Innovation (EFRI)
NSF Emerging Frontiers in Research and Innovation Program Solicitation
Guidance
Standards that would be applied for data format and metadata content
', '', '
NSF Emerging Frontiers in Research and Innovation (EFRI)
NSF Emerging Frontiers in Research and Innovation Program Solicitation
Guidance
Access polices and provision
', '', 'Access policies:
Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. If the data is of a sensitive nature—human subject concerns, potential patentability, species/ecological endangerment concerns—that public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements; anonymiztion of data; restricted access, only available within a secure network). Consider these questions:
Sharing the research with the rest of the scientific community
', '', 'Means of sharing:
The description should be specific and describe what, how, and when the community would have access to the outcome of the project. Will data be accessible on a web page, through publications, databases, via open-access repository, etc.? If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). Consider these questions:
Describe the data that will be collected, and the data and metadata formats and standards used.
', '', 'Data collected:
Describe the data to be collected (actual observations) during your research including amount (if known). Name the type of data, the instrument or collection approach, and how the data will be sampled. If actual data are interpreted, note the interpretation. Describe any quality control measures. Also describe the final derivative products (datasets and software or computer code) and the analysis used including analytical software packages that are required for replication, etc. Describe the format of your data; think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available. For example, for most ecological data, documentation should be structured in Ecological Metadata Language (EML). An example of metadata could also be as simple as a "readme file" to explain variables, structure of the files, etc. Consider these questions:
Describe what physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends.
', '', 'Data storage and preservation:
The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
Describe what media and dissemination methods will be used to make the data and metadata available to others after the grant ends.
', '', 'Dissemination methods:
Describe how and where you will make these data and metadata available to the community. Remember BIO is committed to timely and rapid data distribution; make sure you address how soon your data will be available. Indicate what data will be made available and preserved. Will data be accessible on a web page, by email request, via open-access repository, etc.? Consider these questions:
Describe the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)
', '', 'Policies for sharing:
Describe the policies under which these data will be made available. It is very important, the reason a DMP is required, that you specify how you will share your data with non-group members after the project is completed. If the data is of a sensitive nature—privacy or ecological endangerment concerns, for instance—and public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements, anonymized data, only available within a secure network, etc.). Consider these questions:
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project) after the grant ends.
', '', 'Roles and responsibilities:
Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself.
', '', 'Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer.
', '', 'Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable.
', '', 'NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers.
', '', 'NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like.
', '', 'Each NSF grant contains, as part of the grant terms, an article implementing dissemination and sharing of research results.
', '', '
The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', 'The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', 'Specify the roles and responsibilities of all parties with respect to the DMP activities.
', '', 'Specify the types of data or products that will be generated (e.g., test scores, survey responses, images, data tables, video or audio data, sftware, curricular or exhibit materials).
', '', 'Specify how data or products are to be stored, preserved, and shared.
', '', 'Specify any restrictions on data or product storage, access, preservation, or sharing
', '', 'Specify what data formats will be used (e.g., XML files, websites, image files, data tables, software code, text documents, physical materials).
', '', 'Specify how long access to data and products, and sharing of data or products, will be maintained after the life of the project, and how any associated costs will be covered and by whom.
', '', 'If data or products are to be preserved by a third party, please refer to their preservation plans if available.
', '', 'More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself.
', '', 'Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer.
', '', '
Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable.
', '', '
NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers.
', '', 'NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like.
', '', '
Physics Division PIs should include in their Data Management Plan those aspects of data retention and sharing that would allow them to respond to a question about a published result. Members of formal collaborations may refer to the collaborations existing policies and practices.
', '', '
What types of data, samples, collections, software, materials, etc. will be produced during your project?
This is the most detailed section of the data management plan. Describe the categories of data being collected and how they tie into the data associated with the methods used to collect that data. Expect this section to be the most detailed section, taking up a large portion of your data management plan document.
', 'During this project, soil cores will be collected from three sites representing varying degrees of snow accumulation. Temperature, moisture and active layer thaw depth will be collected to record soil physical properties. Soil samples from each core will be analyzed for carbon concentration, nitrogen concentration and pH.
Aerial photos of each of the three sites will also be taken twice annually to visualize the snow cover. Additional data products that will be made available include data analysis codes in R and high school-level educational materials regarding soil properties in changing climatic conditions in the Arctic.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (959, 132, 611, 'What will be the approximate number and size of data files that will be produced during your project?
', '', 'This section is driven by sampling design, and is based on what you predict you will be collecting. Realistic estimates are sufficient. This section is important because reviewers need to understand what data you plan on collecting and how you plan on managing that data. ', 'In this project, there will be six experimental treatments applied to the Saxifraga cespitosa plants, with four replicates for each treatment collected three times during the year. Therefore, there will be approximately 72 data files each year (6 treatments x 4 replicates x 3 collections per year). The 72 data files will be approximately 720 MB in size.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (960, 132, 611, 'What type of metadata (information others might need to use your data) will be collected during your project?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
', '', 'Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.
The project will collect and record a description of the time of soil core collection in the field, along with the time of soil core processing in the laboratory. The exact locations and conditions of the field sites will be described as well as the laboratory conditions and location of soil sample analysis. A detailed description of the soil core sample collection and processing methods in the field, as well as the laboratory soil carbon and nitrogen concentration collection and processing methods will be included. Units will be recorded for all samples. Soil carbon and nitrogen will be reported in %C and %N, respectively, along with the C:N ratio and the %delta 13C and %delta 15N. Soil depth will be recorded in centimeters.
Quality control procedures will be followed in both the field and the laboratory during sample collection and processing, and the details of these procedures will be included. The decisions for the inclusion of each component of the project, including the specific sampling methods, units, and procedures, will be provided. The hardware and software used will be provided. R Studio will be used for coding and data analysis, with the code shared in a Github repository.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (961, 132, 612, '
What format(s) will data and metadata be collected, processed, and stored in?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
', '', 'Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. Additionally, please provide ORCiD identification for all individuals collecting and analyzing the data for proper citation and credit.
', '
The local and traditional knowledge data will be collected during interviews using tape recording devices. The survey answers will then be transcribed and exported to CSV files for storage. Metadata will be documented in CSV files. The soil core data will be collected by hand in the field and then entered into a CSV file for storage. The soil core metadata will be entered in CSV files along with the metadata. Imagery metadata from the core sites will be encoded in NetCDF files. All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (962, 132, 613, '
1. What parties and individuals will be involved with data management in this project?
2. What will be the roles and responsibilities of each party and or individual with respect to management of the data?
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
', '', 'Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. The purpose of this section is to ensure that the individuals ultimately responsible for ensuring compliance with the data management plan are both aware and agree to their roles.
', 'The project’s principal investigator, Jane Doe, will ultimately be responsible for all of the data management. It is Doe’s responsibility to make sure all of the project team members are taught the proper data management skills and uphold the data management requirements. Doe will delegate data management duties to the laboratory project data manager, Bonnie, along with graduate student, Clyde, working in the field. The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (964, 132, 614, '
How will data be accessed and shared during the course of the project?
Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publicly accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.
NSF Office of Polar Programs Guidelines
', 'During the course of the project, data files will be stored in a laboratory Github repository. The data will initially be stored in Excel files and transferred to CSV files. At the end of each year of data collection, the data files will deposited to a shared file system on the Github repository where all team members can access the files. ', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (963, 132, 614, 'Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research.
', '', '', 'Survey data taken during interviews with the local residents are expected to need provisions for confidentiality due to ethical restrictions and the protection of indigenous knowledge. This sensitive data is governed by an Institutional Review Board policy. Additionally, this project deals with endangered species, so similarly sensitive data, particularly location data, will also be exempted from the archiving requirements set for Arctic Sciences research due to confidentiality and species protection.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (965, 132, 614, '
When is the approximate release date of the data products?
Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
', '', 'NSF Office of Polar Programs Guidelines
', 'The data will be released within two years of data collection.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (966, 132, 615, '
How do you anticipate the data for this project will be used? Consider the following:
The salmon catch data are expected to be used by other researchers studying Arctic food web systems in addition to government agencies with regard to establishing catch limits in the area. Local fishermen and fish modellers may also make use of this data. The data will be added to a long-term data set to continue to observe changes in the region through time.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (967, 132, 615, 'Will any permission restrictions need to be placed on the data? Consider the following:
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data.
', 'All data will be accessible to the public and subject to usage and dissemination restrictions under the CC-0 Public Domain Dedication License.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (968, 132, 616, '
What is the long-term strategy for maintaining, curating, and archiving the data?
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:
The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (969, 133, 617, 'The DMP should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It should also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution or project. Any costs should be explained in the Budget Justification pages.
', '', 'The DMP should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained.
', '', 'SBE is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their DMP statement.
', '', 'The DMP should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders.
', '', 'The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories.
', '', 'More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'What types of data (experimental, computational, or text-based), metadata, samples, physical collections, models, software, curriculum materials, and other materials will be collected and/or generated in the course of the project? The DMP should describe the expected types of data to be retained, managed, and shared, and the plans for doing so. What descriptions of the metadata are needed to make the actual data products useful and reproducible for the general researcher? For collaborative proposals, the DMP should describe the roles and responsibilities of all parties with respect to the management of data (including contingency plans for the departure of key personnel from the project) both during and after the grant cycle.
', '', 'In what format and/or media will the data or products be stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats)? Where data are stored in unusual or not generally accessible formats, how may the data be converted to more accessible formats or otherwise made available to interested parties? When existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies. In general, solutions and remedies to providing data in an accessible format should be offered with minimal added cost.
', '', 'What specific dissemination approaches will be used to make data available and accessible to others, including any pertinent metadata needed to interpret the data? In this case, "available and accessible" refers to data that can be found and obtained without a personal request to the PI, for example by download from a public repository. What plans, if any, are in place for providing access to data, including websites maintained by the research group and contributions to public databases/repositories? For software or code developed as part of the project, include a description of how users can access the code (e.g., licensing, open source) and specific details of the hosting, distribution and dissemination plans. If maintenance of a website or database is the direct responsibility of the research group, what is the period of time the website or database is expected to be maintained? What are the practices or policies regarding the release of POST-AWARD MANAGEMENT data – for example, are they available before or after formal publication? What is the approximate duration of time that the data will be kept private? “Data sharing” refers to the release of data in response to a specific request from an interested party. What are the policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements? Research centers and major partnerships with industry or other user communities should also address how data are to be shared and managed with partners, center members, and other major stakeholders; publication delay policies (if applicable) should be clearly stated.
', '', 'What are your policies regarding the use of data provided via general access or sharing? For data to be deemed “re-usable,” it must be accompanied by any metadata needed to reproduce the data, e.g., the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other pertinent metadata. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should also be clearly articulated. For example, if you plan to provide data and images on your website, will the website contain disclaimers or condition regarding the use of the data in other publications or products?
', '', 'When and how will data be archived and how will access be preserved over time? For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). Where no data or sample repository exists for collected data or samples, metadata should be prepared and made publicly available over the Internet and the PI should employ alternative strategies for complying with the general philosophy of sharing research products and data as described above
', '', 'Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, HD5, Virtual Observatory-compliant tables, XML files, etc.). Include a description of any metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided.
', '', '"Access to data" refers to data made accessible to an interested party without the need for an explicit request from the interested party. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and contributions of your data to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period you plan to maintain the web site or data base. Note that data taken at national or private observatories may already be accessible through a public archive (perhaps after a standard proprietary period). Various forms of data (e.g. FITS images and tables, HD5 or other data tables) also may be deposited with published articles in the AAS journals and other journals. Attention should be paid to making accessible data sets that are products of well-defined surveys. Also describe your practice or policies regarding the release of data, for example whether data are posted before or after formal publication.
"Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. It is preferred that all data products be made available without requiring a special request to investigators.
', '', 'Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website?
', '', 'Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Special attention should be taken to selecting institutional sites that are expected to have a reasonably long lifetime.
', '', 'The Data Management Plan should describe the types of data, metadata, scripts used to generate the data or metadata, experimental results, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project.
', '', 'The Data Management Plan should address the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It should also cover any other types of information that would be maintained and shared regarding data, e.g. the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other metadata.
', '', 'The Data Management Plan should address the policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. It should cover any factors that limit the ability to manage and share data, e.g. legal and ethical restrictions on access to human subject data.
', '', 'The Data Management Plan should address the policies and provision for re-use, re-distribution, and the production of derivatives.
', '', 'The Data Management Plan should address the plans for archiving data, samples, and other research products, and for the preservation of access to them. It should cover the period of time the data will be retained and shared; how data are to be managed, maintained, and disseminated; and mechanisms and formats for storing data and making them accessible to others, which may include third party facilities and repositories.
', '', 'The Data Management Plan should clearly articulate how the PI and co-PIs plan to manage and disseminate data generated by the project. The plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data, and consider changes that would occur should a PI or co-PI leave the institution or project. It should describe how the research team plans to deposit data into any relevant and appropriate disciplinary repositories that are appropriately managed and that are likely to maintain the metadata necessary for future use and discovery. Any costs associated with implementing the DMP should be explained in the Budget Justification.
', '', 'The following questions are intended to assist PIs and panel members to prepare Data Management Plans and to evaluate them during merit review, respectively. The questions are sequential, that is, if (1) applies, then the remaining questions are irrelevant unless (2) also applies or the PI chooses to deposit the data or software in multiple repositories. The more detailed questions, (4)-(6), apply if (1) and (2) do not.
Describe the types of data (including metadata and annotations, primary or analyzed) and products that will be generated by the research, for example description of samples, numerical data on chemical systems such as spectra, chemical and physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, experimental protocols, algorith specifications, database schemas and data tables, data produced by simulations and software. Data and products generated from Broader Impact activities, such as educational materials, participant information, tutorials and other web-based materials, as well as assessment results, should also be included in the DMP.
', '', 'Describe the format and media in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally-accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies to providing data in an accessible format should be provided with minimal added cost.
', '', '"Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases or software repositories (e.g., NMRShiftDB, the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database and Github). For software or code developed as part of the project, include a description of how users can access the code (e.g. licensing, open source) and specific details of the hosting, distribution and dissemination plans. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Note as well any anticipated inclusion of your data in databases that mine the published literature (e.g. PubChem, NIST Chemistry WebBook). Consider using the Digital Object Identifiers (DOI) assignment mechanism not just for journal articles, but for suitably-archived, publishable data sets.
"Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. Discussion on the compliance with the NSFs Public Access Policy is also encouraged.
', '', 'Describe your policies regarding the use of data provided via general access or sharing. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should be defined. For example, if you plan to provide data and images on your website, will the website contain disclaimers or conditions regarding the use of the data in other publications or products?
', '', 'Describe when the data should be archived, how data will be archived, and how preservation of access will be handled. Are there provisions for data backup? Will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? What are the physical and cyber resources and facilities that will be used for data preservation and storage? Will there be an easily accessible index that douments where all archived data are stored and how they can be accessed? What are the roles and responsibilities of all parties with respect to the management and archiving of the data after the grant ends? How long will the data be maintained after the grant ends?
CHE-supported large research centers or other programs may specify more stringent data storage, sharing and archiving procedures for research conducted under their awards. Such requirements will be specified in the program solicitation and award conditions.
', '', 'Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, existence of metadata, etc).
', '', 'Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases, and the mechanism for making the existence of an archive publicly known (e.g. by indicating the data sharing mechanism in publications that recognize NSF support). If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data – for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements.
', '', 'Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website?
', '', 'Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available).
', '', 'If implementing the DMP will incur additional costs to the project this fact should be mentioned in the appropriate section of the plan (for example the cost of setting up and maintaining a web site). Details of the costs must be included in the budget justification in the budget section of the proposal.
', '', 'Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.)
', '', '
Describe the standards to be used for all the data types anticipated, including data or file format and metadata. [Note: Where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies.]
', '', '
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project).
', '', '
Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends.
', '', '
Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights.
', '', '
Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education. Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?)
', '', '
Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES).
', '', 'NSF Division of Ocean Sciences Sample and Data Policy
NSF Frequently Asked Questions (FAQs) for Public Access
NSF Guidance on Data Management Plans
NSF GEO Directorate Data Policies
', 'The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2921, 331, 1498, 'If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions:
If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO along with dataset metadata.
Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available).
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2922, 331, 1499, 'Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them.
', '', 'It may be useful to group data into four categories:
Keep in mind that code or software developed through your project must also be made publicly available in compliance with NSF Policies. Code may be contributed to BCO-DMO or published with a DOI through Zenodo.
If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determined at a later date.
The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).
Observational Datasets:
Experimental Datasets:
Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions:
Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses. Whenever possible, quality flags should be included as columns within each dataset. The use of standard vocabularies/naming conventions is highly recommended.
Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2924, 331, 1501, 'Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following:
BCO-DMO “How-To” Pages
NSF Division of Ocean Sciences Sample and Data Policy
NSF Frequently Asked Questions (FAQs) for Public Access
', '
The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2925, 331, 1502, 'Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following:
Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.
Data Sharing via BCO-DMO
If the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.
Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.
BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.
Refer to the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.
Genomic Data and Other Specialized Repositories
Provisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.
BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.
Underway Shipboard Data
All routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.
Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers and related metadata will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO online Submission Tool. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publicly available without restriction once submitted to the public repositories.
Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use).
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2926, 331, 1503, 'Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following:
R2R will ensure that the original underway measurements are archived permanently at NCEI and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2927, 331, 1504, 'Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following:
', '
Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2971, 335, 1518, 'List the types of data and samples to be collected and/or generated. The listing of each data/sample type should briefly identify what metadata will be provided and when data/sample preparation will be considered complete. (Definitions of “data” and “samples” are explained above within “EAR requirements.”) For proposals providing community-serving infrastructure or research services, the DMP should describe the data/sample types to be managed and what guidance or support will be provided to help users meet their data/sample sharing obligations. EAR recognizes that data/samples may undergo multiple transformations in the research process (including destructive analyses), and disciplinary expectations for assignment of metadata and retention of intermediate data and sample products may vary.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2972, 335, 1518, 'For each data or sample type, identify which personnel and institution(s) will be designated for its management, including contingency plans for the departure of key personnel from the project. For collaborative projects, PI(s) of the award(s) associated with the designated personnel and institution(s) are ultimately responsible for overseeing and reporting on their data and sample management activities.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2973, 335, 1519, 'For each data type listed, identify an appropriate long-lived FAIR-aligned repository for data deposit, the timeframe for public data access, and the expected period of data preservation. For each sample type listed, identify an appropriate long-lived FAIRaligned repository for indexing sample metadata, the location for sample storage (preferably a repository appropriate for the specific sample type), and the expected period of sample preservation. (Required timeframes for data/sample access are specified above within “EAR Requirements.”) Many repositories commit to preserve access to data/samples indefinitely; any deviations from this expectation should be explained. PIs are encouraged to coordinate with designated repositories in advance of planned data/sample submission.
', '', 'NSF EAR Guidance:
All new data resulting from the project must be made publicly accessible within two (2) years after completion of data collection or generation, via appropriate long-lived FAIRaligned repositories. Expected timelines for data collection or generation may vary by data type and should align with appropriate disciplinary expectations. All new data collected via continuing observations, large-scale community projects, or RAPID awards must be made accessible as close to the time of initial collection as is practicable. All data in support of peer-reviewed scholarly publications resulting from the project must also be made publicly accessible at or before the time of publication. Exceptions to this policy must be justified (e.g., if an appropriate repository does not exist, or if data access must be restricted). “Data available upon request” is not acceptable.
Metadata describing all new samples resulting from the project must be publicly indexed within two (2) years after sample collection is considered complete, via appropriate long-lived FAIR-aligned repositories. Metadata describing samples collected via continuing observations, large-scale community projects, or RAPID awards must be indexed and made accessible as close to the time of collection as is practicable. All sample metadata in support of peer-reviewed scholarly publications must also be publicly indexed at or before the time of publication. Publicly indexed sample metadata should specify provisions for sample access, including the expected period and location of sample preservation, preferably via a repository appropriate for the specific sample type. The samples themselves should also be made publicly accessible within the above timeframes; situations in which samples cannot be made publicly accessible should be explained.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2974, 335, 1519, 'In most cases, it is sufficient for the DMP to identify the repository(ies) to be used and the timeframe for access and preservation for each type of data/sample identified. In these cases, the selected repository(ies) should align with FAIR principles and community-specific standards. Occasionally, appropriate long-lived FAIR-aligned repositories do not exist for certain types of data or samples. In such cases, it may be necessary to adopt alternative approaches to data access and retention, such as via use of a local computer server. In such cases, the DMP should explain how the proposed approach fulfills important attributes for FAIR-aligned repositories, consistent with OSTP guidance on “Desirable Characteristics of Data Repositories for Federally Funded Research.”9 These attributes include, but are not limited to, the following:
• Findability. Data should be findable via standard search tools, such as through the assignment of globally unique persistent identifiers (e.g., Digital Object Identifiers (DOIs) and International Geo Sample Numbers (IGSNs)) and rich metadata that is indexed in a searchable resource.
• Accessibility. Data should be publicly accessible to other researchers, at no more than incremental cost, within the specified timeframe. Any data access limitations must be justified. “Data available upon request” is not acceptable.
• Interoperability. To ensure interoperability, data should be described via appropriate metadata standards, in alignment with expectations of the associated scientific discipline(s).
• Reusability. To facilitate the broadest possible data reuse, data should be assigned clear and accessible usage licenses and metadata descriptors that identify provenance. EAR expects the adoption of unrestrictive open licenses except with specific justification.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (2975, 336, 1520, 'The Division of Earth Sciences requires that full data sets, derived data products (e.g. model results, output, and workflows), software, and physical collections must be made publicly accessible within two (2) years of final collection.
', '', 'Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures.
', '', 'Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', '1A. Types and amount of scientific data expected to be generated in the project:
Summarize the types and estimated amount of scientific data expected to be generated in the project.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3347, 362, 1662, '1B. Of the generated scientific data in 1.A, the scientific data that will be preserved and shared, and the associated rationale:
Describe which types of scientific data from the project will be preserved and shared and briefly provide the rationale for this decision.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3348, 362, 1662, '1C. Metadata and associated documentation:
Briefly list the metadata (provides information about the scientific data) and any associated documentation (e.g., study protocols, research methods, and data-collection instruments) that will be made accessible to facilitate interpretation of the preserved and shared scientific data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3349, 362, 1663, '2A. Specialized tools, Software/Code, and/or Services for Access or Interpretation
State whether specialized tools, software/code and/or services are needed to access, manipulate, or interpret the preserved and shared data, and if so, provide the name(s) of the tool(s) and software/code or services, and specify how they can be found, accessed, and used (a link may be adequate).
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3350, 362, 1663, '2B. Software/Code and/or Other Digital Products Produced:
State software/code and/or other digital products expected to result from the successful execution of the project and to be distributed according to FAIR principles. Include any license intended to be used for the release and a justification for the choice, and how the product will be made accessible (include methods used to advertise to the broader community). Machine learning models should ideally be distributed along with associated training data.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3351, 362, 1664, '3. State what common data standards will be applied to the preserved and shared scientific data, and associated metadata to enable interoperability of datasets and resources and describe how these data standards will be applied. If applicable, indicate that no consensus standards exist.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3352, 362, 1665, '4A. Repository where scientific data and metadata will be available for reuse:
Provide the name of the repository(ies) from which preserved and shared scientific data and metadata arising from the project will be available for reuse; see Dear Colleague Letter: Effective Practices for Making Research Data Discoverable and Citable (Data Sharing) and Desirable Characteristics of Data Repositories for Federally Funded Research.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3353, 362, 1665, '4B. How scientific data will be findable and identifiable:
Describe how the scientific data will be findable and identifiable, i.e., via a persistent unique identifier (e.g., DOI), listing in a registry, or other standard indexing techniques.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3354, 362, 1665, '4C. When and for how long the scientific data will be made broadly available:
Describe when the scientific data will be made broadly available (i.e., no later than when an associated publication appears or end of the performance period, whichever comes first) and for how long data will be available. Include any external factors that may affect time of appearance.
', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, 0, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO questions (id, templateId, sectionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, isDirty, createdById, created, modifiedById, modified) VALUES (3355, 362, 1666, '5A. Factors affecting subsequent access, distribution, or reuse of scientific data:
NSF expects that in drafting Plans, researchers should maximize the appropriate sharing of scientific data. Describe and clearly justify any applicable factors or data-use limitations affecting subsequent access, distribution, or reuse of scientific data.
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Describe the types of data and samples expected to result from the proposed work.
', '', '', 0, 1, @default_funder2_id, NOW(), @default_funder2_id, NOW()); +INSERT INTO versionedSections (id, versionedTemplateId, sectionId, name, introduction, requirements, guidance, bestPractice, displayOrder, createdById, created, modifiedById, modified) VALUES (5390, 833, 1519, 'Data/sample deposit, access, and preservation', 'Describe how each type of data or sample will be deposited, made accessible, and preserved
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', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.Consider the following:
Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'Describe the format of your data and how it will be documented. Think about what details (metadata) someone else would need to be able to use these files. For example, you may need a "readme file" to explain variables, structure of the files, etc. Metadata associated with the data should conform to community standards and the requirements of the host repository. NSF does not currently specify a single metadata standard. However, any acceptable minimum set of data elements would include the names of all authors, date of publication or release, and Universal Resource Locator (URL) or other persistent identifier, as required by Biographical Sketches in proposals (Section 3.2.3 and Grant Proposal Guide, Chapter II C.2.f.i (c)).
Consider these questions:
Policies for access and sharing; Provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', 'Explain how and when the data will become available. Will data be accessible on a web page, by email request, via open-access repository etc.? If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). And if the data is of a sensitive nature - human subject concerns, potential patentability, species/ecological endangerment concerns - that public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements; anonymizing data; restricted access, only available within a secure network).
Practices governing use of embargos and delayed data release vary widely across the research communities supported by NSF and should be discussed as part of the DMP. For large-scale projects that are supported primarily to generate data for community use, the timing of release will be part of the award terms and conditions and clearly stated in the public award abstracts. NSF recognizes that some classes of data, particularly those that relate to human subjects, education, personally identifiable information, national security, or proprietary interests, may be subject to restrictions. Such restrictions must be described in the DMP and changes addressed in annual and final reports.Small Business Innovation Research (SBIR)/Small Business Technology Transfer (STTR) proposals and any other proposal may allow for exceptions for proprietary or otherwise restricted data, including but not limited to personally identifiable information, business confidential information, security, among other concerns outlined in section 4.a. of the OSTP memo. Any such data management issues as well as conditions that might affect, delay, or limit data sharing should be discussed in the DMP. Coordination with the Cognizant Program Officer prior to submitting the proposal is also advised. Consider these questions:
Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Policies for reuse:
Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Consider the following:
Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details.There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on. In general, good practice calls for duplicating the collection at a geographically distinct location and for regular monitoring and format migration, given exigencies of media degradation and format obsolescence.
Consider the following:
What kind of data will be collected, standards employed, and for how long will data be retained?
', '', '
DataONE Best Practice: Define Expected Data Outcomes and Types
What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data?
', '', '
re3data: Registry of data repositories
DataONE Best Practice: Document and Store Data Using Stable File Formats
Describe standards to be used for data and metadata format and content.
', '', '
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Suitable Repositories for your Data
What will be the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)?
', '', '
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Data Sensitivity
What are the rights and obligations of all parties with respect to their roles in and responsibilities for the management and retention of research data (including contingency plans for the departure of key personnel from the project)?
', '', '
DataONE Best Practice: Identify Suitable Repositories for your Data
DataONE Best Practice: Revisit Data Management Plan Throughout the Project Life Cycle
Preservation of all data, samples, physical collections and other supporting materials needed for long-term earth science research and education is required of all EAR-supported researchers.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.
Consider the following:
Data archives must include easily accessible information about data holdings, including quality assessments, supporting ancillary information, and guidance and aids for locating and obtaining data.
', '', 'Data and metadata standards:
Datasets need metadata to be usable. Think about what details (metadata) someone else would need to be able to use these files. For example, you may need a readme.txt file to explain variables, structure of the files, etc.
It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures.
', '', 'Policies for access and sharing:
Specify how you will share your data with others after the project is completed. Ideally, you will use an appropriate open-access discipline-specific data repository; regardless of the repository you choose, describe how you chose it. Consider these questions:
For those programs in which selected principle investigators have initial periods of exclusive data use, data should be made openly available as soon as possible, but no later than two (2) years after the data were collected. This period may be extended under exceptional circumstances, but only by agreement between the Principal Investigator and the National Science Foundation. For continuing observations or for long-term (multi-year) projects, data are to be made public annually.
', '', 'Describe policies surrounding the re-use of your data – the EAR division is specifically interested in how soon you will make your data available. If you will not be making the data available for re-use immediately, explain why. Remember that EAR specifies that you must make your data available no later than two years after your research is complete. If there are other policy issues regarding data access and re-use (ethical or privacy issues, for instance) elaborate on them here. Consider these questions:
Remember - Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories.
', '', 'Archiving and Preservation (EAR):
Describe your long-term strategy for archiving and preserving your data. EAR encourages PIs to submit data to an “EAR-specified” repository. Consider the following:
The Data Management Plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It must also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution.
', '', 'Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
Consider the following:
The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.
Consider the following:
The Data Management Plan should describe the period of data retention. Minimum data retention of research data is three years after conclusion of the award or three years after public release, whichever is later. Public release of data should be at the earliest reasonable time. A reasonable standard of timeliness is to make the data accessible immediately after publication, where submission for publication is also expected to be timely. Exceptions requiring longer retention periods may occur when data supports patents, when questions arise from inquiries or investigations with respect to research, or when a student is involved, requiring data to be retained a timely period after the degree is awarded. Research data that support patents should be retained for the entire term of the patent. Longer retention periods may also be necessary when data represents a large collection that is widely useful to the research community. For example, special circumstances arise from the collection and analysis of large, longitudinal data sets that may require retention for more than three years. Project data-retention and data-sharing policies should account for these needs.
', '', 'Period of data retention:
Estimate how long your data will be kept after the completion of your research. Describe any institutional or project-based policies on data retention that might apply.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF ENG directorate guidance (PDF)
Guidance
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
The Data Management Plan should describe the specific data formats, media, including any metadata.
', '', 'Data formats and metadata:
Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Metadata may entail descriptions of research details such as: experiments, apparatuses, computational codes, etc. Consider these questions:
The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. In collaborative proposals or proposals involving sub-awards, the lead PI is responsible for assuring data storage and access.
', '', 'The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
Consider the following:
Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.
Consider the following:
Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'Data and metadata standards:
Datasets need metadata to be usable. Think about what details (metadata) someone else would need to be able to use these files. For example, you may need a readme.txt file to explain variables, structure of the files, etc.
Policies for access and sharing; Provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', 'Explain how and when the data will become available. If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). And if the data is of a sensitive nature, address the means by which access will be restricted. Consider these questions:
Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Policies for reuse:
Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Consider the following:
Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.
Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details.
There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on. In general, good practice calls for duplicating the collection at a geographically distinct location and for regular monitoring and format migration, given exigencies of media degradation and format obsolescence.
Consider the following:
The Data Management Plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It must also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution.
', '', 'Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
Consider the following:
The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained.
', '', 'Expected data (SBE):
Give a short description of what data will mean in the context of your research project. Explain what types of data you plan to generate including size, file formats, and number of files. Briefly describe your methods for collecting data. Consider the following:
SBE is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their DMP statement.
', '', 'Data retention:
Describe how long you plan to retain the data produced or used in your research. If you plan to embargo the data for a period of time after the research is completed, describe why this is necessary. Consider the following:
The Data Management Plan should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders.
', '', 'The DMP should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center affiliates, and other major stakeholders.
Ideally, data formats will be chosen that are openly and freely available, and/or non-proprietary in nature. Consider the following:
Describe how you will ensure dissemination of your data. Consider the following:
The Data Management Plan should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories.
', '', 'The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
Consider the following:
More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'Describe here any additional program-specific data management requirements. If none exist you may leave this section blank.
Please note the Rigor and Reproducibility requirements that involve updates to grant application instructions and review criteria (but not Data Sharing Plans).
Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.
Consider the following:
Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies).
', '', 'Data and metadata standards:
Datasets need metadata to be usable. Think about what details (metadata) someone else would need to be able to use these files. For example, you may need a readme.txt file to explain variables, structure of the files, etc.
Policies for access and sharing; Provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.
', '', 'Explain how and when the data will become available. If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). And if the data is of a sensitive nature, address the means by which access will be restricted. Consider these questions:
Policies and provisions for re-use, re-distribution, and the production of derivatives.
', '', 'Policies for reuse:
Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Consider the following:
Plans for archiving data, samples, and other research products, and for preservation of access to them.
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.
Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details.
There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on. In general, good practice calls for duplicating the collection at a geographically distinct location and for regular monitoring and format migration, given exigencies of media degradation and format obsolescence.
Consider the following:
Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Products of research:
Describe what data or other research products you will generate in the course of your project. Include the size or amount of data produced, the type of data files that will be generated, and where and when the data will be produced. Examples of research products include observational data, results from models, data generated from previous observations or models, physical samples, software, curriculum materials, etc. Consider the following:
Describe the format in which the data or products are stored (e.g., ASCII, HTML, FITS, VO compliant tables, XML files, etc.). Include a description of the metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided.
', '', 'Data formats and metadata:
Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Metadata may entail descriptions of research details such as: experiments, apparatuses, computational codes, etc. Consider these questions:
"Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or data base is expected to be maintained. Note that data taken at national or private observatories may be accessible through public archives (perhaps after a standard proprietary period). Various forms of data (e.g., FITS images and tables, other data tables) also may be deposited with published articles in the AAS journals and other journals. Particular attention should be paid to data sets that are products of well-defined surveys. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. "Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing, including where applicable provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements.
', '', 'Describe how you will make the data available to other researchers, as well as to the general public. Consider what data will be available (and in what formats) and where (on your website, available via ftp download, via e-mail, or another way). Please keep in mind that you are expected to adequately provide responses for both how you plan on making your data accessible without a specific request from a researcher, and how you will be able to provide data to the public. Make sure to mention how long the data will be kept private before making it available, and if different data products will be available on different schedules (e.g. raw data vs. processed data). Use this section to also explain policies for the protection of proprietary data, issues of privacy and confidentiality, and intellectual property as their impact on the dissemination of your data. Consider these questions:
Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website?
', '', 'Policies for reuse:
Explain how the policies you outlined in the section above can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you will be restricting access, use or dissemination of the data, you must explain how you will codify and communicate these terms. Consider these questions:
Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available.
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details.There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on. In general, good practice calls for duplicating the collection at a geographically distinct location and for regular monitoring and format migration, given exigencies of media degradation and format obsolescence.
Consider the following:
Describe the types of data and products that will be generated in the research, for example numerical data on chemical systems such as spectra, diffraction patterns, physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, computational strategies, final or intermediate numerical results from theoretical calculations, software, and curriculum materials.
', '', 'Products of research:
Describe what data or other research products you will generate in the course of your project. Include the size or amount of data produced, the type of data files that will be generated, and where and when the data will be produced. Examples of research products include observational data, results from models, data generated from previous observations or models, physical samples, software, curriculum materials, etc. Consider the following:
Describe the format in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. You may also comment on the current or anticipated need for interested parties outside of your laboratory to access your primary data.
', '', 'Data formats and metadata:
Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Metadata may entail descriptions of research details such as: experiments, apparatuses, computational codes, etc. Consider these questions:
"Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases (e.g., the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database). Also note if you submit your data in the form of tables, graphs, computer code or other format to the supplementary materials sections of peer-reviewed journals. Describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Finally, note as well any anticipated inclusion of your data into databases that mine the published literature (e.g., PubChem, NIST Chemistry WebBook). "Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing, including where applicable provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements.
', '', 'Describe how you will make the data available to other researchers, as well as to the general public. Consider what data will be available (and in what formats) and where (on your website, available via ftp download, via e-mail, or another way). Please keep in mind that you are expected to adequately provide responses for both how you plan on making your data accessible without a specific request from a researcher, and how you will be able to provide data to the public. Make sure to mention how long the data will be kept private before making it available, and if different data products will be available on different schedules (e.g. raw data vs. processed data). Use this section to also explain policies for the protection of proprietary data, issues of privacy and confidentiality, and intellectual property as their impact on the dissemination of your data. Consider these questions:
Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? Describe these disclaimers and/or terms of use.
', '', 'Policies for reuse:
Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Consider the following:
Describe how data will be archived and how preservation of access will be handled. For example, will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed?
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.
Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details.
There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on. In general, good practice calls for duplicating the collection at a geographically distinct location and for regular monitoring and format migration, given exigencies of media degradation and format obsolescence.
Consider the following:
The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, or other materials generated by your project. Any data collection required by the program announcement should be incorporated into the proposal’s Data Management Plan. For example, the management of assessment, evaluation, or monitoring data required for all projects within a given program should be addressed in the data management plan. Describe your plan for managing the data.
', '', 'Data generated:
Describe the data you plan to generate, including amount and type. Data types could include spreadsheets, interview transcripts, text files, historical documents, diaries, field notes, geospatial data, citations, software code, algorithms, etc. Identify your methods for collecting data. Consider the following:
EHR is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their Data Management Plan.
', '', 'Data retention:
Describe how long you plan to retain the data produced or used in your research. If you plan to embargo the data for a period of time after the research is completed, describe why this is necessary. Consider the following:
EHR is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their Data Management Plan.
', '', 'Data retention:
Describe how long you plan to retain the data produced or used in your research. If you plan to embargo the data for a period of time after the research is completed, describe why this is necessary. Consider the following:
The Data Management Plan should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. Data on EHR projects involving human subjects should be made available to the public subject to constraints imposed by IRB decisions. Other data, such as software, publications, and curricula, should be made available subject to intellectual property rights.
', '', 'The DMP should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center affiliates, and other major stakeholders.
Ideally, data formats will be chosen that are openly and freely available, and/or non-proprietary in nature. Consider the following:
Describe how you will ensure dissemination of your data. Consider the following:
The Data Management Plan should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories.
', '', 'The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
Consider the following:
More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'Describe here any additional program-specific data management requirements. If none exist you may leave this section blank.
Please note the Rigor and Reproducibility requirements that involve updates to grant application instructions and review criteria (but not Data Sharing Plans).
More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans.
', '', 'Describe here any additional program-specific data management requirements. If none exist you may leave this section blank.
Please note the Rigor and Reproducibility requirements that involve updates to grant application instructions and review criteria (but not Data Sharing Plans).
The Data Management Plan should clearly articulate how the PI and co-PIs plan to manage and disseminate data generated by the project. The plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data, and consider changes that would occur should a PI or co-PI leave the institution or project. Any costs should be explained in the Budget Justification pages.
', '', 'Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
Consider the following:
The Data Management Plan should clearly articulate how the PI and co-PIs plan to manage and disseminate data generated by the project. The plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data, and consider changes that would occur should a PI or co-PI leave the institution or project. Any costs should be explained in the Budget Justification pages.
', '', 'Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
Consider the following:
The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project. It should then describe the expected types of data to be retained and shared, and the plans for doing so. The DMP should cover how data are to be managed and maintained during the project.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.
Consider the following:
The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project. It should then describe the expected types of data to be retained and shared, and the plans for doing so. The DMP should cover how data are to be managed and maintained during the project.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based.
Consider the following:
The Data Management Plan should describe the period of time the data will be retained and shared; factors that limit the ability to manage and share data, e.g., legal and ethical restrictions on access to human subjects data; and provisions for appropriate protection of privacy, confidentiality, security, and intellectual property.
', '', 'Explain how and when the data will become available. If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). And if the data is of a sensitive nature, address the means by which access will be restricted. Consider these questions:
The Data Management Plan should describe the mechanisms and formats for storing data and making them accessible to others, which may include third party facilities and repositories; and other types of information that would be maintained and shared regarding data, e.g. the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other metadata.
', '', 'The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
Consider the following:
Note that individual solicitations may have additional data management plan requirements. If guidance specific to the program is not available, then the requirements established in the Grant Proposal Guide apply.
', '', 'Describe here any additional program-specific data management requirements. If none exist you may leave this section blank. Please note the Rigor and Reproducibility requirements that involve updates to grant application instructions and review criteria (but not Data Sharing Plans).
Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Products of research:
Describe what data or other research products you will generate in the course of your project. Include the size or amount of data produced, the type of data files that will be generated, and where and when the data will be produced. Examples of research products include observational data, results from models, data generated from previous observations or models, physical samples, software, curriculum materials, etc. Consider the following:
Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, etc). What metadata will be part of the data sets produced?
', '', 'Data formats and metadata:
Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Metadata may entail descriptions of research details such as: experiments, apparatuses, computational codes, etc. Consider these questions:
Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data—for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements.
', '', 'Describe how you will make the data available to other researchers, as well as to the general public. Consider what data will be available (and in what formats) and where (on your website, available via ftp download, via e-mail, or another way). Please keep in mind that you are expected to adequately provide responses for both how you plan on making your data accessible without a specific request from a researcher, and how you will be able to provide data to the public. Make sure to mention how long the data will be kept private before making it available, and if different data products will be available on different schedules (e.g. raw data vs. processed data). Use this section to also explain policies for the protection of proprietary data, issues of privacy and confidentiality, and intellectual property as their impact on the dissemination of your data. Consider these questions:
Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website?
', '', 'Policies for reuse:
Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Consider the following:
Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available).
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details.There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on. In general, good practice calls for duplicating the collection at a geographically distinct location and for regular monitoring and format migration, given exigencies of media degradation and format obsolescence.
Consider the following:
Types of data to be produced
', '', '
NSF Emerging Frontiers in Research and Innovation (EFRI)
NSF Emerging Frontiers in Research and Innovation Program Solicitation
Guidance
Standards that would be applied for data format and metadata content
', '', '
NSF Emerging Frontiers in Research and Innovation (EFRI)
NSF Emerging Frontiers in Research and Innovation Program Solicitation
Guidance
Access polices and provision
', '', 'Access policies:
Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. If the data is of a sensitive nature—human subject concerns, potential patentability, species/ecological endangerment concerns—that public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements; anonymiztion of data; restricted access, only available within a secure network). Consider these questions:
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (89, 17, 89, 20, '
Sharing the research with the rest of the scientific community
', '', 'Means of sharing:
The description should be specific and describe what, how, and when the community would have access to the outcome of the project. Will data be accessible on a web page, through publications, databases, via open-access repository, etc.? If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). Consider these questions:
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Describe the data that will be collected, and the data and metadata formats and standards used.
', '', 'Data collected:
Describe the data to be collected (actual observations) during your research including amount (if known). Name the type of data, the instrument or collection approach, and how the data will be sampled. If actual data are interpreted, note the interpretation. Describe any quality control measures. Also describe the final derivative products (datasets and software or computer code) and the analysis used including analytical software packages that are required for replication, etc. Describe the format of your data; think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available. For example, for most ecological data, documentation should be structured in Ecological Metadata Language (EML). An example of metadata could also be as simple as a "readme file" to explain variables, structure of the files, etc. Consider these questions:
Describe what physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends.
', '', 'Data storage and preservation:
The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (105, 20, 105, 36, '
Describe what media and dissemination methods will be used to make the data and metadata available to others after the grant ends.
', '', 'Dissemination methods:
Describe how and where you will make these data and metadata available to the community. Remember BIO is committed to timely and rapid data distribution; make sure you address how soon your data will be available. Indicate what data will be made available and preserved. Will data be accessible on a web page, by email request, via open-access repository, etc.? Consider these questions:
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (106, 20, 106, 37, '
Describe the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)
', '', 'Policies for sharing:
Describe the policies under which these data will be made available. It is very important, the reason a DMP is required, that you specify how you will share your data with non-group members after the project is completed. If the data is of a sensitive nature—privacy or ecological endangerment concerns, for instance—and public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements, anonymized data, only available within a secure network, etc.). Consider these questions:
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project) after the grant ends.
', '', 'Roles and responsibilities:
Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (302, 55, 268, 2922, '
Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them.
', '', 'It may be useful to group data into four categories:
The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).Observational Datasets:
Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES).
', '', '
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF GEO Directorate guidance
Data Policy Compliance:
The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy.
Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions: (1) Which file formats will be used to store your data? (2) What type of contextual details (metadata) will you document and how? (3) Are there specific data or metadata standards that you will be adhering to? (4) Will you be using or creating a data dictionary, code list, or glossary? (5) What types of quality control will be used? How will data quality be assessed and flagged?
', '', 'Data and Metadata Formats and Standards:
Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses.
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
BCO-DMO Guidance on Organizing Data in a Spreadsheet
DMPTool Guidance on File Formats
Data and Metadata Formats and Standards:
Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures.
Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following: (1) What is your long-term strategy for maintaining, curating, and archiving the data? (2) What archive(s) have you identified as a place to deposit data and other research products?
', '', 'Plans for Archiving:
After data contributed to BCO-DMO are online and fully documented, BCO-DMO ensures that the data are archived properly at the appropriate National Data Center (e.g. NODC) for long-term archive preservation.
The Rolling Deck to Repository program (R2R) is responsible for archiving routine underway data at the appropriate national archive, including the National Geophysical Data Center (NGDC) and the National Oceanographic Data Center (NODC).
See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.
Plans for Archiving:
R2R will ensure that the original underway measurements are archived permanently at NODC and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data.
Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following: (1) If there are multiple investigators involved, what are the data management responsibilities of each person? (2) Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
', '', '
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
Roles and Responsibilities:
Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive.
If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions: (1) How will pre-cruise planning be coordinated? (e.g. email, teleconference, workshop) (2) What types of sampling instruments will be deployed on the cruise? (3) How will the cruise event log be recorded? (e.g. the Rolling Deck to Repository (R2R) event logger application, an Excel spreadsheet, or paper logs) (4) Will you prepare a cruise report?
', '', 'Pre-cruise planning:
If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO, along with the project and dataset metadata. Information on how to contribute deployment metadata to BCO-DMO is available on the BCO-DMO website at http://www.bco-dmo.org/how-get-started.
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
R2R Scientific Sampling Event Log
BCO-DMO DMP Suggestions for Proposals Involving a Research Cruise (PDF)
IMBER Data Management Cookbook
ROSCOP (Report of Observations/Samples collected by Oceanographic Programmes) Cruise Summary Form
Pre-cruise planning:
Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available).
Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following: (1) How will data be shared among project participants during the data collection and analysis phases? (e.g. web page, shared network drive) (2) How/where will data be stored and backed-up? (3) If data volumes will be significant, what is the estimated total file size?
', '', '
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
DMPTool Guidance on Security and Storage
Data Storage and Access During the Project:
The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive.
Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following: (1) When will data be made publicly available and how? Identify the data repositories you plan to use to make data available. (2) Are the data sensitive in nature (e.g. endangered species concerns, potential patentability)? If so, is public access inappropriate and how will access be provided? (e.g. formal consent agreements, restricted access) (3) Will any permission restrictions (such as an embargo period) need to be placed on the data? If so, what are the reasons and what is the duration of the embargo? (4) Who holds intellectual property rights to the data and how might this affect data access? (5) Who is likely to be interested in re-using the data? What are the foreseeable re-uses of the data?
', '', 'Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.Data Sharing via BCO-DMOIf the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.Genomic Data and Other Specialized RepositoriesProvisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.Underway Shipboard DataAll routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.NSF Division of Ocean Sciences Sample and Data PolicyFrequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOData Repositories List (created by Integrated Earth Data Applications (IEDA))Terms of Use for Data at BCO-DMOR2R Cruise CatalogDMPTool Guidance on Copyright and PrivacyCreative Commons License TypesUniversity-National Oceanographic Laboratory System (UNOLS)National Center for Biotechnology Information (NCBI)GenBankLong Term Ecological Research (LTER) Network Data Portal
', 'Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO Dataset Metadata submission form. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publically available without restriction once submitted to the public repositories.Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use).
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (505, 93, 430, 2153, 'Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.)
', '', 'Describe the data to be collected (actual observations) during your research including amount (if known). Name the type of data, the instrument or collection approach, and how the data will be sampled. If actual data are interpreted, note the interpretation. Describe any quality control measures. Also describe the final derivative products (datasets and software or computer code) and the analysis used including analytical software packages that are required for replication, etc. Describe data (both digital and analog) and physical materials (samples and collections) gathered or generated during the time of the award. Consider these questions:
Describe the standards to be used for all the data types anticipated, including data or file format and metadata.
', '', 'Standards Formats:
Describe the format of your data; think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available. For example, for most ecological data, documentation should be structured in Ecological Metadata Language (EML). An example of metadata could also be as simple as a "readme file" to explain variables, structure of the files, etc.
Consider these questions:
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project).
', '', 'Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data. Consider the following:
Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends.
', '', 'Describe how and where you will make these data and metadata available to the community. Remember BIO is committed to timely and rapid data distribution; make sure you address how soon your data will be available. Indicate what data will be made available and preserved. Will data be accessible on a web page, by email request, via open-access repository, etc.? Consider these questions:
Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights.
', '', 'Describe the policies under which these data will be made available. It is very important, the reason a DMP is required, that you specify how you will share your data with non-group members after the project is completed. If the data is of a sensitive nature—privacy or ecological endangerment concerns, for instance—and public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements, anonymized data, only available within a secure network, etc.). Consider these questions:
Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education.
', '', 'Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?)Describe your long-term strategy for storing, archiving and preserving the data you will generate or use. Consider the following:
Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.)
', '', 'Data Collected BIO 2015:
Describe the data to be collected (actual observations) during your research including amount (if known). Name the type of data, the instrument or collection approach, and how the data will be sampled. If actual data are interpreted, note the interpretation. Describe any quality control measures. Also describe the final derivative products (datasets and software or computer code) and the analysis used including analytical software packages that are required for replication, etc. Describe data (both digital and analog) and physical materials (samples and collections) gathered or generated during the time of the award.Consider these questions:What data will be generated in the research?What data types will you be creating or capturing? (e.g. experimental measures, qualitative, raw, processed)How will you capture or create the data? (This should cover content selection, instrumentation, technologies and approaches chosen, metNSF BIO GuidanceNSF Public Access: Frequently Asked QuestionsESA Data Sharing ResourcesDataONE Best PracticesUSGS Data Management Best Practices
Describe the standards to be used for all the data types anticipated, including data or file format and metadata.
', '', 'Standards Formats:
Describe the format of your data; think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available. For example, for most ecological data, documentation should be structured in Ecological Metadata Language (EML). An example of metadata could also be as simple as a "readme file" to explain variables, structure of the files, etc.
Consider these questions:
Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project).
', '', 'Roles and responsibilities:
Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data.
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (948, 139, 663, 2156, '
Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends.
', '', 'Dissemination methods:
Describe how and where you will make these data and metadata available to the community. Remember BIO is committed to timely and rapid data distribution; make sure you address how soon your data will be available. Indicate what data will be made available and preserved. Will data be accessible on a web page, by email request, via open-access repository, etc.? Consider these questions:
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (949, 139, 664, 2157, '
Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights.
', '', 'Policies for sharing:
Describe the policies under which these data will be made available. It is very important, the reason a DMP is required, that you specify how you will share your data with non-group members after the project is completed. If the data is of a sensitive nature—privacy or ecological endangerment concerns, for instance—and public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements, anonymized data, only available within a secure network, etc.). Consider these questions:
Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education.
', '', 'Archiving Storage Preservation:
Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?)
Describe your long-term strategy for storing, archiving and preserving the data you will generate or use. Consider the following:
', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE()); -INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (968, 143, 683, 1502, '
Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Describe what data or other research products you will generate in the course of your project. Include the size or amount of data produced, the type of data files that will be generated, and where and when the data will be produced. Examples of research products include observational data, results from models, data generated from previous observations or models, physical samples, software, curriculum materials, etc.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Define Expected Data Outcomes and Types
Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, etc). What metadata will be part of the data sets produced?
', '', 'Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Metadata may entail descriptions of research details such as: experiments, apparatuses, computational codes, etc.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Document and Store Data Using Stable File Formats
Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data—for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements.
', '', 'Describe how you will make the data available to other researchers, as well as to the general public. Consider what data will be available (and in what formats) and where (on your website, available via ftp download, via e-mail, or another way). Please keep in mind that you are expected to adequately provide responses for both how you plan on making your data accessible without a specific request from a researcher, and how you will be able to provide data to the public. Make sure to mention how long the data will be kept private before making it available, and if different data products will be available on different schedules (e.g. raw data vs. processed data). Use this section to also explain policies for the protection of proprietary data, issues of privacy and confidentiality, and intellectual property as their impact on the dissemination of your data. NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Suitable Repositories for your Data
Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website?
', '', 'Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Data Sensitivity
Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available).
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details. There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Identify Suitable Repositories for your Data
DataONE Best Practice: Revisit Data Management Plan Throughout the Project Life Cycle
Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials.
', '', 'Describe what data or other research products you will generate in the course of your project. Include the size or amount of data produced, the type of data files that will be generated, and where and when the data will be produced. Examples of research products include observational data, results from models, data generated from previous observations or models, physical samples, software, curriculum materials, etc.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Define Expected Data Outcomes and Types
Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, etc). What metadata will be part of the data sets produced?
', '', 'Describe the format of your data, and think about what details (metadata) someone else would need to be able to use these files. Metadata may entail descriptions of research details such as: experiments, apparatuses, computational codes, etc.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Document and Store Data Using Stable File Formats
Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data—for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements.
', '', 'Describe how you will make the data available to other researchers, as well as to the general public. Consider what data will be available (and in what formats) and where (on your website, available via ftp download, via e-mail, or another way). Please keep in mind that you are expected to adequately provide responses for both how you plan on making your data accessible without a specific request from a researcher, and how you will be able to provide data to the public. Make sure to mention how long the data will be kept private before making it available, and if different data products will be available on different schedules (e.g. raw data vs. processed data). Use this section to also explain policies for the protection of proprietary data, issues of privacy and confidentiality, and intellectual property as their impact on the dissemination of your data. NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Suitable Repositories for your Data
Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website?
', '', 'Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
DataONE Best Practice: Identify Data Sensitivity
Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available).
', '', 'Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details. There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF AGS division guidance
NSF GEO Directorate guidance
AGS Advice
DataONE Best Practice: Identify Suitable Repositories for your Data
DataONE Best Practice: Revisit Data Management Plan Throughout the Project Life Cycle
Types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project.
', '', 'Provide a description of the data you will collect or re-use, including the file types, dataset size, number of expected files or sets, and content. Data types could include text, spreadsheets, images, 3D models, software, audio files, video files, reports, surveys, patient records, etc. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. NSF Data Management FAQ Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Describe the format of your data and how it will be documented. Think about what details (metadata) someone else would need to be able to use these files. For example, you may need a "readme file" to explain variables, structure of the files, etc. Metadata associated with the data should conform to community standards and the requirements of the host repository. NSF does not currently specify a single metadata standard. However, any acceptable minimum set of data elements would include the names of all authors, date of publication or release, and Universal Resource Locator (URL) or other persistent identifier, as required by Biographical Sketches in proposals (Section 3.2.3 and Grant Proposal Guide, Chapter II C.2.f.i (c)).NSF Data Management FAQ Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Explain how and when the data will become available. Will data be accessible on a web page, by email request, via open-access repository etc.? If there is an embargo period for sharing the data, make sure you provide details explaining this delay (e.g. publisher, political, commercial, patent reasons). And if the data is of a sensitive nature - human subject concerns, potential patentability, species/ecological endangerment concerns - that public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements; anonymizing data; restricted access, only available within a secure network). Policies and provisions for re-use, re-distribution, and the production of derivatives. Explain how the policies outlined in the previous question can be applied to the re-use and re-distribution of your data. Identify who will be allowed to use your data, how they will be allowed to use your data and whether or not they will be allowed to disseminate your data. If you are planning on restricting access, use or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions. Plans for archiving data, samples, and other research products, and for preservation of access to them. Provide a description of your long-term strategy for archiving and preserving the data you plan to generate/use. Data that underlie the findings reported in a journal article or conference paper should be deposited in accordance with the policies of the publication and according to the procedures laid out in the DMP included in the proposal that led to the award on which the research is based. All data resulting from the research funded by the award, whether or not the data support a publication, should be deposited at the appropriate repository as explained in the DMP.Rarely does NSF expect that retention of all data that are streamed from an instrument or created in the course of an experiment or survey will be required. See your specific directorate or solicitation for details. The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Policies and provisions for re-use, re-distribution, and the production of derivatives. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Plans for archiving data, samples, and other research products, and for preservation of access to them. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials. AGS Advice to PIs on Data Management Plans (MS-Word)NSF Geosciences (GEO) Home, Atmospheric & Geospace Sciences. https://www.nsf.gov/geo/geo-data-policies/ags/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, etc). AGS Advice to PIs on Data Management Plans (MS-Word)NSF Geosciences (GEO) Home, Atmospheric & Geospace Sciences. https://www.nsf.gov/geo/geo-data-policies/ags/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data—for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements. AGS Advice to PIs on Data Management Plans (MS-Word)NSF Geosciences (GEO) Home, Atmospheric & Geospace Sciences. https://www.nsf.gov/geo/geo-data-policies/ags/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website? AGS Advice to PIs on Data Management Plans (MS-Word)NSF Geosciences (GEO) Home, Atmospheric & Geospace Sciences. https://www.nsf.gov/geo/geo-data-policies/ags/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). AGS Advice to PIs on Data Management Plans (MS-Word)NSF Geosciences (GEO) Home, Atmospheric & Geospace Sciences. https://www.nsf.gov/geo/geo-data-policies/ags/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website? Directorate of Mathematical and Physical Sciences Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Directorate of Mathematical and Physical Sciences Specify how data or products are to be stored, preserved, and shared. The DMP should describe dissemination approaches that will be used to make data and metadata avilable to others. As appropriate, the DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories. Anticipated costs for data or material management should be list in the proposal Budget and explained in the Budget Justification (and not in the DMP). Research centers and major partnerships with industry or other use communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders.Data storage and preservation:The DMP should describe physical and cyber resources and facilities that will be used to effectively preserve and store research data. These can include third-party facilities and repositories. Specify how long access to data and products, and sharing of data or products, will be maintained after the life of the project, and how any associated costs will be covered and by whom. The data management plan should clearly state how and when data and other materials will be released, and how long they will be stored or archived.Data retention: More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans. Additional data management requirements:Describe here any additional program-specific data management requirements. If none exist you may leave this section blank. Please note the Rigor and Reproducibility requirements that involve updates to grant application instructions and review criteria (but not Data Sharing Plans). Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.) Data Collected BIO 2015: Describe the standards to be used for all the data types anticipated, including data or file format and metadata. Standards Formats: Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project). Roles and responsibilities: Explain how the responsibilities regarding the management of your data will be delegated. This should include time allocations, project management of technical aspects, training requirements, and contributions of non-project staff - individuals should be named where possible. Remember that those responsible for long-term decisions about your data will likely be the custodians of the repository/archive you choose to store your data. While the costs associated with your research (and the results of your research) must be specified in the Budget Justification portion of the proposal, you may want to reiterate who will be responsible for funding the management of your data. ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF Grant Proposal Guide
NSF Data Management FAQ
NSF - Dissemination of research results ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF Grant Proposal Guide
NSF Data Management FAQ
NSF - Dissemination of research results
DataONE Best Practice: Identify and Use Relevant Metadata Standards ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Practices governing use of embargos and delayed data release vary widely across the research communities supported by NSF and should be discussed as part of the DMP. For large-scale projects that are supported primarily to generate data for community use, the timing of release will be part of the award terms
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF Grant Proposal Guide
NSF Data Management FAQ
NSF - Dissemination of research results
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF Grant Proposal Guide
NSF Data Management FAQ
NSF - Dissemination of research results
DataONE Best Practice: Identify Data Sensitivity
There are several technical strategies for achieving long-term preservation including redundancy, dark archives, secure data centers, and so on.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF Grant Proposal Guide
NSF Data Management FAQ
NSF - Dissemination of research results
re3data: Registry of data repositories
DataONE Best Practice: Identify Suitable Repositories for your Data
DataONE Best Practice: Identify Data with Long-Term Value
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Consider the following:What is the long-term strategy for maintaining, curating, and archiving the data?Which archive/repository/database have you identified as a place to deposit data?What procedures does your intended long-term data storage facility have in place for preservation and backup?How long will/should data be kept beyond the life of the project?What data will be preserved for the long-term?On what basis will data be selected for long-term preservation?What metadata/documentation will be submitted alongside the data or created on deposit/transformation in order to make the data reusable?Outline the staff/organizational roles and responsibilities for implementing this data management plan.NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF EHR directorate guidance (PDF)
Guidance
ICPSR Guidelines for Effective DMPs
re3data: Registry of data repositories
DataONE Best Practice: Identify Suitable Repositories for your Data
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Describe how long you plan to retain the data produced or used in your research. If you plan to embargo the data for a period of time after the research is completed, describe why this is necessary. Consider the following:How long will the original data collector/creator/principal investigator retain the right to use the data before opening it up to wider use?Explain details of any embargo periods for political/commercial/patent or publisher reasons.
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF EHR directorate guidance (PDF)
Guidance
ICPSR Guidelines for Effective DMPs
DataONE Best Practice: Sharing Data: Legal and Policy Considerations
NSF Data Management FAQ
NSF - Dissemination of results
NSF Grant Proposal Guide on DMPs
NSF EHR directorate guidance (PDF)
Guidance
ICPSR Guidelines for Effective DMPs
DataONE Best Practice: Revisit Data Management Plan Throughout the Project Life Cycle
Describe the data to be collected (actual observations) during your research including amount (if known). Name the type of data, the instrument or collection approach, and how the data will be sampled. If actual data are interpreted, note the interpretation. Describe any quality control measures. Also describe the final derivative products (datasets and software or computer code) and the analysis used including analytical software packages that are required for replication, etc. Describe data (both digital and analog) and physical materials (samples and collections) gathered or generated during the time of the award.Consider these questions:What data will be generated in the research?What data types will you be creating or capturing? (e.g. experimental measures, qualitative, raw, processed)How will you capture or create the data? (This should cover content selection, instrumentation, technologies and approaches chosen, metNSF BIO GuidanceNSF Public Access: Frequently Asked QuestionsESA Data Sharing ResourcesDataONE Best PracticesUSGS Data Management Best Practices
Describe the format of your data; think about what details (metadata) someone else would need to be able to use these files. Describe the structural standards that you will apply in making data and metadata available. For example, for most ecological data, documentation should be structured in Ecological Metadata Language (EML). An example of metadata could also be as simple as a "readme file" to explain variables, structure of the files, etc.
Consider these questions: Which file formats will you use for your data and why? What form will the metadata describing/documenting your data take? How will you create or capture these details? Which metadata standards will you use and why have you chosen them? (e.g. accepted domain-local standards, widespread usage) What contextual details (metadata) are needed to make the data you capture or collect meaningful?
NSF BIO Guidance
NSF Public Access: Frequently Asked Questions
ESA Data Sharing Resources
DataONE Best Practices
USGS Data Management Best Practices
Guidance
Consider the following:
NSF BIO Guidance
NSF Public Access: Frequently Asked Questions
ESA Data Sharing Resources
DataONE Best Practices
USGS Data Management Best Practices
Guidance
Describe how and where you will make these data and metadata available to the community. Remember BIO is committed to timely and rapid data distribution; make sure you address how soon your data will be available. Indicate what data will be made available and preserved. Will data be accessible on a web page, by email request, via open-access repository, etc.? Consider these questions:What data will be made available from the study and preserved for the long-term?How and when will you make the data available? (Include resources needed to make the data available: equipment, systems, expertise, etc.)What transformations will be necessary to prepare data for preservation / data sharing?What metadata/ documentation will be submitted alongside the data or created on deposit/ transformation in order to make the data reusable?What related information will be deposited?What is the process for gaining access to the data?H
NSF BIO Guidance
NSF Public Access: Frequently Asked Questions
ESA Data Sharing Resources
DataONE Best Practices
USGS Data Management Best Practices
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Describe the policies under which these data will be made available. It is very important, the reason a DMP is required, that you specify how you will share your data with non-group members after the project is completed. If the data is of a sensitive nature—privacy or ecological endangerment concerns, for instance—and public access is inappropriate, address here the means by which granular control and access will be achieved (e.g. formal consent agreements, anonymized data, only available within a secure network, etc.). Consider these questions:Will any permission restrictions need to be placed on the data?Are there ethical and privacy issues? If so, how will these be resolved?What have you done to comply with your obligations in your IRB Protocol?Who will hold the intellectual property rights to the data and how might this affect data access?What and who are the intended or foreseeable uses/users of the data?
Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education.
', '', 'Archiving Storage Preservation: The Division of Earth Sciences requires that full data sets, derived data products (e.g. model results, output, and workflows), software, and physical collections must be made publicly accessible within two (2) years of final collection. Data and Sample Policy, Division of Earth Sciences, NSF https://www.nsf.gov/geo/geo-data-policies/ear/ear-data-policy-sep2017.pdfEAR Division Data Sharing Policy Appendix (September 2017) (MS-Excel)NSF Geosciences (GEO) Home. https://www.nsf.gov/geo/geo-data-policies/ear/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Data and Sample Policy, Division of Earth Sciences, NSF https://www.nsf.gov/geo/geo-data-policies/ear/ear-data-policy-sep2017.pdfEAR Division Data Sharing Policy Appendix (September 2017) (MS-Excel)NSF Geosciences (GEO) Home. https://www.nsf.gov/geo/geo-data-policies/ear/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures. Data and Sample Policy, Division of Earth Sciences, NSF https://www.nsf.gov/geo/geo-data-policies/ear/ear-data-policy-sep2017.pdfEAR Division Data Sharing Policy Appendix (September 2017) (MS-Excel)NSF Geosciences (GEO) Home. https://www.nsf.gov/geo/geo-data-policies/ear/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Policies and provisions for re-use, re-distribution, and the production of derivatives. Data and Sample Policy, Division of Earth Sciences, NSF https://www.nsf.gov/geo/geo-data-policies/ear/ear-data-policy-sep2017.pdfEAR Division Data Sharing Policy Appendix (September 2017) (MS-Excel)NSF Geosciences (GEO) Home. https://www.nsf.gov/geo/geo-data-policies/ear/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 Policies and provisions for re-use, re-distribution, and the production of derivatives. Data and Sample Policy, Division of Earth Sciences, NSF https://www.nsf.gov/geo/geo-data-policies/ear/ear-data-policy-sep2017.pdfEAR Division Data Sharing Policy Appendix (September 2017) (MS-Excel)NSF Geosciences (GEO) Home. https://www.nsf.gov/geo/geo-data-policies/ear/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060 The DMP should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It should also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution or project. Data management plan for SBE proposals and awards. https://www.nsf.gov/news/news_summ.jsp?cntn_id=118038Social, behavioral and economic sciences (SBE) Directorate. https://www.nsf.gov/dir/index.jsp?org=SBEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1115, 161, 758, 970, ' The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained. Data management plan for SBE proposals and awards. https://www.nsf.gov/news/news_summ.jsp?cntn_id=118038Social, behavioral and economic sciences (SBE) Directorate. https://www.nsf.gov/dir/index.jsp?org=SBEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 SBE is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their DMP statement. Data management plan for SBE proposals and awards. https://www.nsf.gov/news/news_summ.jsp?cntn_id=118038Social, behavioral and economic sciences (SBE) Directorate. https://www.nsf.gov/dir/index.jsp?org=SBEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 The Data Management Plan should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. Data management plan for SBE proposals and awards. https://www.nsf.gov/news/news_summ.jsp?cntn_id=118038Social, behavioral and economic sciences (SBE) Directorate. https://www.nsf.gov/dir/index.jsp?org=SBEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 The Data Management Plan should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories. Data management plan for SBE proposals and awards. https://www.nsf.gov/news/news_summ.jsp?cntn_id=118038Social, behavioral and economic sciences (SBE) Directorate. https://www.nsf.gov/dir/index.jsp?org=SBEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans. Data management plan for SBE proposals and awards. https://www.nsf.gov/news/news_summ.jsp?cntn_id=118038Social, behavioral and economic sciences (SBE) Directorate. https://www.nsf.gov/dir/index.jsp?org=SBEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Describe the types of data (including metadata and annotations, primary or analyzed) and products that will be generated by the research, for example description of samples, numerical data on chemical systems such as spectra, chemical and physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, experimental protocols, algorith specifications, database schemas and data tables, data produced by simulations and software. Data and products generated from Broader Impact activities, such as educational materials, participant information, tutorials and other web-based materials, as well as assessment results, should also be included in the DMP.You may request funds to cover costs of publication, page charges, or preparation of data as a direct cost in your budget proposal, which is evaluated as part of the merit review process. Any costs associated with implementing the DMP should be explained in the Budget Justification. NSF Division of Chemistry (CHE) Advice to Principle Investigators on Data Management Plans. January 2, 2018. division guidance (PDF)NSF Mathematical & Physical Sciences, Chemistry (CHE). https://www.nsf.gov/div/index.jsp?div=CHEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Describe the format and media in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally-accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies to providing data in an accessible format should be provided with minimal added cost. NSF Division of Chemistry (CHE) Advice to Principle Investigators on Data Management Plans. January 2, 2018. division guidance (PDF)NSF Mathematical & Physical Sciences, Chemistry (CHE). https://www.nsf.gov/div/index.jsp?div=CHEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases or software repositories (e.g., NMRShiftDB, the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database and Github). For software or code developed as part of the project, include a description of how users can access the code (e.g. licensing, open source) and specific details of the hosting, distribution and dissemination plans. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Note as well any anticipated inclusion of your data in databases that mine the published literature (e.g. PubChem, NIST Chemistry WebBook). Consider using the Digital Object Identifiers (DOI) assignment mechanism not just for journal articles, but for suitably-archived, publishable data sets."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. Discussion on the compliance with the NSFs Public Access Policy is also encouraged. NSF Division of Chemistry (CHE) Advice to Principle Investigators on Data Management Plans. January 2, 2018. division guidance (PDF)NSF Mathematical & Physical Sciences, Chemistry (CHE). https://www.nsf.gov/div/index.jsp?div=CHEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 Describe your policies regarding the use of data provided via general access or sharing. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should be defined. For example, if you plan to provide data and images on your website, will the website contain disclaimers or conditions regarding the use of the data in other publications or products? NSF Division of Chemistry (CHE) Advice to Principle Investigators on Data Management Plans. January 2, 2018. division guidance (PDF)NSF Mathematical & Physical Sciences, Chemistry (CHE). https://www.nsf.gov/div/index.jsp?div=CHEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 Describe when the data should be archived, how data will be archived, and how preservation of access will be handled. Are there provisions for data backup? Will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? What are the physical and cyber resources and facilities that will be used for data preservation and storage? Will there be an easily accessible index that douments where all archived data are stored and how they can be accessed? What are the roles and responsibilities of all parties with respect to the management and archiving of the data after the grant ends? How long will the data be maintained after the grant ends?CHE-supported large research centers or other programs may specify more stringent data storage, sharing and archiving procedures for research conducted under their awards. Such requirements will be specified in the program solicitation and award conditions. NSF Division of Chemistry (CHE) Advice to Principle Investigators on Data Management Plans. January 2, 2018. division guidance (PDF)NSF Mathematical & Physical Sciences, Chemistry (CHE). https://www.nsf.gov/div/index.jsp?div=CHEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 Specify the roles and responsibilities of all parties with respect to the DMP activities. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. Specify the types of data or products that will be generated (e.g., test scores, survey responses, images, data tables, video or audio data, sftware, curricular or exhibit materials). Specify any restrictions on data or product storage, access, preservation, or sharing Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. The Data Management Plan should describe the types of data, metadata, scripts used to generate the data or metadata, experimental results, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project. Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEComputer & Information Science & Engineering (CISE) Active Funding Opportunities. https://www.nsf.gov/funding/pgm_list.jsp?org=ciseProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1130, 163, 774, 1413, ' The Data Management Plan should address the policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The DMP should address the policies and provision for re-use, re-distribution, and the production of derivatives. Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEComputer & Information Science & Engineering (CISE) Active Funding Opportunities. https://www.nsf.gov/funding/pgm_list.jsp?org=ciseProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The Data Management Plan should address the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project) after the grant ends. Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEComputer & Information Science & Engineering (CISE) Active Funding Opportunities. https://www.nsf.gov/funding/pgm_list.jsp?org=ciseProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 Specify what data formats will be used (e.g., XML files, websites, image files, data tables, software code, text documents, physical materials). The DMP should describe data formats and media approaches that will be used to make data and metadata available to others. If data or products are to be preserved by a third party, please refer to their preservation plans if available. Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. NSF DMR division guidance on DMPs January 2011(PDF)NSF Mathematical & Physical Sciences, Division of Materials Research (DMR) https://www.nsf.gov/div/index.jsp?div=DMRProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. NSF DMR division guidance on DMPs January 2011(PDF)NSF Mathematical & Physical Sciences, Division of Materials Research (DMR) https://www.nsf.gov/div/index.jsp?div=DMRProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. NSF DMR division guidance on DMPs January 2011(PDF)NSF Mathematical & Physical Sciences, Division of Materials Research (DMR) https://www.nsf.gov/div/index.jsp?div=DMRProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. NSF DMR division guidance on DMPs January 2011(PDF)NSF Mathematical & Physical Sciences, Division of Materials Research (DMR) https://www.nsf.gov/div/index.jsp?div=DMRProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. NSF DMR division guidance on DMPs January 2011(PDF)NSF Mathematical & Physical Sciences, Division of Materials Research (DMR) https://www.nsf.gov/div/index.jsp?div=DMRProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period of time the web site or data base is expected to be maintained. Note that data taken at national or private observatories may be accessible through public archives (perhaps after a standard proprietary period). Various forms of data (e.g.FITS image and tables, other data tables) also may be deposted with published articles in the AAS journals and other journals. Particular attention should be paid to data sets that are products of well-defined surveys. Also describe your practice before or after formal publication."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your polies for data sharing, including where applicable provisions for protection of privacy, confidentiality, intellectual propoerty, national security, or other rights or requirements. Directorate of Mathematical and Physical Sciences Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, VO-compliant tables, XML files, etc.). Include a description of the metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided. Directorate of Mathematical and Physical Sciences Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials. Directorate of Mathematical and Physical Sciences The DMP should clearly articulate how "sharing of primary data" is to be implemented. It should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It must also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution. Any costs should be explained in the Budget Justification pages. Data Management for NSF Engineering Directorate Proposals and Awards. https://nsf.gov/eng/general/ENG_DMP_Policy.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained. Data Management for NSF Engineering Directorate Proposals and Awards. https://nsf.gov/eng/general/ENG_DMP_Policy.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf17060NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jsp The DMP should describe the period of data retention. Minimum data retention of research data is three years after conclusion of the award or three years after public release, whichever is later. Data Management for NSF Engineering Directorate Proposals and Awards. https://nsf.gov/eng/general/ENG_DMP_Policy.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf17060NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jsp The DMP should describe the specific data formats, media, and dissemination approaches that will be used to make data available to others, including any metadata. Policies for public access and sharing should be described, including provisions for appropirate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. Publication delay policies (if applicable) must be clearly stated. Investigators are expected to submit significant findings for publications quickly that are consistent with the publication delay obligations of key partners, such as industrial members of a research center. Data Management for NSF Engineering Directorate Proposals and Awards. https://nsf.gov/eng/general/ENG_DMP_Policy.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf17060NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jsp The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. In collaborative proposals or proposals involving sub-awards, the lead PI is responsible for assuring data storage and access. Data Management for NSF Engineering Directorate Proposals and Awards. https://nsf.gov/eng/general/ENG_DMP_Policy.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jsp Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans If implementing the DMP will incur additional costs to the project this fact should be mentioned in the appropriate section of the plan (for example the cost of setting up and maintaining a web site). Details of the costs must be included in the budget justification in the budget section of the proposal. AGS Advice to PIs on Data Management Plans (MS-Word)NSF Geosciences (GEO) Home, Atmospheric & Geospace Sciences. https://www.nsf.gov/geo/geo-data-policies/ags/index.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The Data Management Plan should address the physical and/or cyber resources and facilities (including those supplied by third parties) that will be used to store and preserve the data after the grant ends. NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspData Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The DMP should address the plans for archiving data, samples, and other research products, and for the preservation of access to them after the award ends. Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEComputer & Information Science & Engineering (CISE) Active Funding Opportunities. https://www.nsf.gov/funding/pgm_list.jsp?org=ciseProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The DMP should address the plans for archiving data, samples, and other research products, and for the preservation of access to them after the award ends. Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEComputer & Information Science & Engineering (CISE) Active Funding Opportunities. https://www.nsf.gov/funding/pgm_list.jsp?org=ciseProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041NSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 The Data Management Plan should address the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Data Management Guidance for CISE Proposals and Awards. https://www.nsf.gov/cise/cise_dmp.jspComputer & Information Science & Engineering Home: https://www.nsf.gov/dir/index.jsp?org=CISEComputer & Information Science & Engineering (CISE) Active Funding Opportunities. https://www.nsf.gov/funding/pgm_list.jsp?org=ciseProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4 Specify the roles and responsibilities of all parties with respect to the DMP activities. Data Management for NSF EHR Directorate Proposals and Awards 03/10/2011. tps://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2j Specify the types of data or products that will be generated (e.g., test scores, survey responses, images, data tables, video or audio data, sftware, curricular or exhibit materials). Data Management for NSF EHR Directorate Proposals and Awards 03/10/2011. tps://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2j Specify how data or products are to be stored, preserved, and shared. Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf17060NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jsp Specify any restrictions on data or product storage, access, preservation, or sharing Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf17060 ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1236, 178, 848, 575, ' Specify what data formats will be used (e.g., XML files, websites, image files, data tables, software code, text documents, physical materials). Data Management for NSF EHR Directorate Proposals and Awards 03/10/2011. tps://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2j Specify how long access to data and products, and sharing of data or products, will be maintained after the life of the project, and how any associated costs will be covered and by whom. Data Management for NSF EHR Directorate Proposals and Awards 03/10/2011. tps://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2j If data or products are to be preserved by a third party, please refer to their preservation plans if available. Data Management for NSF EHR Directorate Proposals and Awards 03/10/2011. tps://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2j More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans. Data Management for NSF EHR Directorate Proposals and Awards 03/10/2011. tps://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdfProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2j If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions: (1) How will pre-cruise planning be coordinated? (e.g. email, teleconference, workshop) (2) What types of sampling instruments will be deployed on the cruise? (3) How will the cruise event log be recorded? (e.g. the Rolling Deck to Repository (R2R) event logger application, an Excel spreadsheet, or paper logs) (4) Will you prepare a cruise report? If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO, along with the project and dataset metadata. Information on how to contribute deployment metadata to BCO-DMO is available on the BCO-DMO website at http://www.bco-dmo.org/how-get-started.NSF Division of Ocean Sciences Sample and Data Policy Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available). Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them. Description of Data Types: It may be useful to group data into four categories: If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determin Description of data types: The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August). Observational Datasets: ', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1275, 184, 879, 2923, ' Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions: (1) Which file formats will be used to store your data? (2) What type of contextual details (metadata) will you document and how? (3) Are there specific data or metadata standards that you will be adhering to? (4) Will you be using or creating a data dictionary, code list, or glossary? (5) What types of quality control will be used? How will data quality be assessed and flagged? Data and Metadata Formats and Standards: Data and Metadata Formats and Standards: Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following: (1) How will data be shared among project participants during the data collection and analysis phases? (e.g. web page, shared network drive) (2) How/where will data be stored and backed-up? (3) If data volumes will be significant, what is the estimated total file size? Data Storage and Access During the Project: Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following: (1) When will data be made publicly available and how? Identify the data repositories you plan to use to make data available. (2) Are the data sensitive in nature (e.g. endangered species concerns, potential patentability)? If so, is public access inappropriate and how will access be provided? (e.g. formal consent agreements, restricted access) (3) Will any permission restrictions (such as an embargo period) need to be placed on the data? If so, what are the reasons and what is the duration of the embargo? (4) Who holds intellectual property rights to the data and how might this affect data access? (5) Who is likely to be interested in re-using the data? What are the foreseeable re-uses of the data? Mechanisms and Policies for Access and Sharing: Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions. If the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded Mechanisms and Policies for Access and Sharing: Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO Dataset Metadata submission form. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publically available without restriction once submitted to the pub Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following: (1) What is your long-term strategy for maintaining, curating, and archiving the data? (2) What archive(s) have you identified as a place to deposit data and other research products? Plans for Archiving: After data contributed to BCO-DMO are online and fully documented, BCO-DMO ensures that the data are archived properly at the appropriate National Data Center (e.g. NODC) for long-term archive preservation. The Rolling Deck to Repository program (R2R) is responsible for archiving routine underway data at the appropriate national archive, including the National Geophysical Data Center (NGDC) and the National Oceanographic Data Center (NODC). See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples. Plans for Archiving: Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following: (1) If there are multiple investigators involved, what are the data management responsibilities of each person? (2) Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan? Roles and Responsibilities: Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES). The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy. Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.) Biological Sciences Guidance on Data Management Plans. https://www.nsf.gov/bio/biodmp.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Biological Sciences (BIO) Home. https://www.nsf.gov/dir/index.jsp?org=BIO Describe the standards to be used for all the data types anticipated, including data or file format and metadata. Biological Sciences Guidance on Data Management Plans. https://www.nsf.gov/bio/biodmp.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Biological Sciences (BIO) Home. https://www.nsf.gov/dir/index.jsp?org=BIO Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project). Biological Sciences Guidance on Data Management Plans. https://www.nsf.gov/bio/biodmp.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Biological Sciences (BIO) Home. https://www.nsf.gov/dir/index.jsp?org=BIO Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends. Biological Sciences Guidance on Data Management Plans. https://www.nsf.gov/bio/biodmp.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Biological Sciences (BIO) Home. https://www.nsf.gov/dir/index.jsp?org=BIO ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (1292, 186, 894, 2157, ' Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights. Biological Sciences Guidance on Data Management Plans. https://www.nsf.gov/bio/biodmp.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060NSF Biological Sciences (BIO) Home. https://www.nsf.gov/dir/index.jsp?org=BIO Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education. Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?) Biological Sciences Guidance on Data Management Plans. https://www.nsf.gov/bio/biodmp.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.NSF Dissemination and Sharing of Research Results, NSF Data Sharing Policy. https://www.nsf.gov/bfa/dias/policy/dmp.jspov/publications/pub_summ.jsp?ods_key=nsf17060NSF Biological Sciences (BIO) Home. https://www.nsf.gov/dir/index.jsp?org=BIO Physics Division PIs should include in their Data Management Plan those aspects of data retention and sharing that would allow them to respond to a question about a published result. Members of formal collaborations may refer to the collaboration\'s existing policies and practices. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. Directorate of Mathematical and Physical Sciences Division of Mathematical Sciences (DMS). Advice to PIs on Data Management Plans January 2, 2018. https://www.nsf.gov/bfa/dias/policy/dmpdocs/dms.pdfMathematical & Physical Sciences (MPS). Mathmatical Sciences (DMS). https://www.nsf.gov/mps/dms/about.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. Directorate of Mathematical and Physical Sciences Division of Mathematical Sciences (DMS). Advice to PIs on Data Management Plans January 2, 2018. https://www.nsf.gov/bfa/dias/policy/dmpdocs/dms.pdfMathematical & Physical Sciences (MPS). Mathmatical Sciences (DMS). https://www.nsf.gov/mps/dms/about.jspProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans Each NSF grant contains, as part of the grant terms, an article implementing dissemination and sharing of research results. Directorate of Mathematical and Physical Sciences Division of Physics (PHY) Advice to PIs on Data Management Plans Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials. Directorate of Mathematical and Physical Sciences Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, VO-compliant tables, XML files, etc.). Include a description of the metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided. Directorate of Mathematical and Physical Sciences "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period of time the web site or data base is expected to be maintained. Note that data taken at national or private observatories may be accessible through public archives (perhaps after a standard proprietary period). Various forms of data (e.g.FITS image and tables, other data tables) also may be deposted with published articles in the AAS journals and other journals. Particular attention should be paid to data sets that are products of well-defined surveys. Also describe your practice before or after formal publication."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your polies for data sharing, including where applicable provisions for protection of privacy, confidentiality, intellectual propoerty, national security, or other rights or requirements. Directorate of Mathematical and Physical Sciences Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website? Directorate of Mathematical and Physical Sciences Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Directorate of Mathematical and Physical Sciences The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Policies and provisions for re-use, re-distribution, and the production of derivatives. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 Plans for archiving data, samples, and other research products, and for preservation of access to them. Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041 The Division of Earth Sciences requires that full data sets, derived data products (e.g. model results, output, and workflows), software, and physical collections must be made publicly accessible within two (2) years of final collection. Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures. Policies and provisions for re-use, re-distribution, and the production of derivatives. Policies and provisions for re-use, re-distribution, and the production of derivatives. Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. Each NSF grant contains, as part of the grant terms, an article implementing dissemination and sharing of research results. Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES). The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy. If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions:How will pre-cruise planning be coordinated? (e.g. email, teleconference, workshop)What types of sampling instruments will be deployed on the cruise?How will the cruise event log be recorded? (e.g. the Rolling Deck to Repository (R2R) event logger application, an Excel spreadsheet, or paper logs)Will you prepare a cruise report?', '', ' If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO, along with the project and dataset metadata. Information on how to contribute deployment metadata to BCO-DMO is available on the BCO-DMO website at http://www.bco-dmo.org/how-get-started.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOR2R Scientific Sampling Event LogBCO-DMO DMP Suggestions for Proposals Involving a Research Cruise (PDF)IMBER Data Management CookbookROSCOP (Report of Observations/Samples collected by Oceanographic Programmes) Cruise Summary Form', ' Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available). Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them. It may be useful to group data into four categories:Observational (e.g. in-situ, collected in the field). Examples may include: shipboard underway data; mesozooplankton samples collected by a net system; copepod specimens collected, identified, and preserved; hydrographic casts; alongtrack data; remote sensing (e.g. ocean color); acoustic data.Experimental (e.g. generated in a lab or under controlled conditions). Examples: controlled carbonate chemistry experiments; DNA and RNA sequences.Simulations (e.g. machine-generated). Example: models and their output.Derived (e.g. synthesized from existing datasets). Examples: compiled database, products, reports.If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determined at a later date.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMO The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).Observational Datasets:CTD and Niskin bottle data: CTD data collected using a SeaBird SBE CTD package; processing to be done using SeaBird’s SeaSave software; data will include standard environmental measurements (such as pressure, temperature, salinity, fluorescence). File types: Raw (.con, .hdr, .hex, .bl) and processed and .cnv, .asc, .btl) ASCII files. Repository: BCO-DMOEvent log: Cruise scientific sampling event log; will include event numbers, start/end dates, times & locations of instrument deployments. Will be recorded using the R2R event logger (if available) and on paper log sheets. File types: Excel file converted to .csv; scanned PDFs. Repository: BCO-DMO and Rolling Deck to Repository (R2R).Cruise underway data: Routine underway data collected along the ship’s track (including meteorological data, sea surface temperature, salinity, fluorescence, ADCP). Will be collected by the shipboard instrumentation. File types: .csv ASCII files. Repository: BCO-DMO and R2R.Zooplankton sampling logs and images: Zooplankton will be sampled via Reeve net trawls and MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System) tows during the cruise. Species identified, tow numbers, locations, depths, dates, and times will be recorded by hand on log sheets. Information from log will be transferred into an Excel spreadsheet. Photographs of each tow/trawl will be taken on the ship using a digital camera. File types: PDF files of scanned log sheets; Excel files of sampling logs; images (.jpg files). Repository: BCO-DMO.Experimental Datasets:Pteropod respiration: Physiological experiments carried out on pteropods captured at sea raised under controlled pCO2 conditions; dataset will include data on the experimental treatments and the observed respiration rates. Animals will be captured using a Reeve Net or MOCNESS. Experiments will be conducted in the ship’s lab. File types: Excel file(s). Repository: BCO-DMO.Genetic sequencing: mRNA and DNA sequences from animals collected at sea. Sequencing will be performed at the PI’s lab in Woods Hole, MA following the research cruise. File types: Short-read archive (.sra) and .fasta files. Repository: NCBI; accession numbers to be provided to BCO-DMO.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2242, 228, 1266, 2923, ' Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions:Which file formats will be used to store your data?What type of contextual details (metadata) will you document and how?Are there specific data or metadata standards that you will be adhering to?Will you be using or creating a data dictionary, code list, or glossary?What types of quality control will be used? How will data quality be assessed and flagged?', '', ' Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOBCO-DMO Guidance on Organizing Data in a Spreadsheet', ' Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures. Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following:How will data be shared among project participants during the data collection and analysis phases? (e.g. web page, shared network drive)How/where will data be stored and backed-up?If data volumes will be significant, what is the estimated total file size?', '', ' The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive. Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following:When will data be made publicly available and how? Identify the data repositories you plan to use to make data available.Are the data sensitive in nature (e.g. endangered species concerns, potential patentability)? If so, is public access inappropriate and how will access be provided? (e.g. formal consent agreements, restricted access)Will any permission restrictions (such as an embargo period) need to be placed on the data? If so, what are the reasons and what is the duration of the embargo?Who holds intellectual property rights to the data and how might this affect data access?Who is likely to be interested in re-using the data? What are the foreseeable re-uses of the data?', '', ' Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.Data Sharing via BCO-DMOIf the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.Genomic Data and Other Specialized RepositoriesProvisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.Underway Shipboard DataAll routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOData Repositories List (created by Integrated Earth Data Applications (IEDA))Terms of Use for Data at BCO-DMOR2R Cruise CatalogCreative Commons License TypesUniversity-National Oceanographic Laboratory System (UNOLS)National Center for Biotechnology Information (NCBI)GenBankLong Term Ecological Research (LTER) Network Data Portal', ' Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO Dataset Metadata submission form. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publically available without restriction once submitted to the public repositories.Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use). Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following:What is your long-term strategy for maintaining, curating, and archiving the data?What archive(s) have you identified as a place to deposit data and other research products?', '', ' R2R will ensure that the original underway measurements are archived permanently at NCEI and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data. Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following:If there are multiple investigators involved, what are the data management responsibilities of each personWho will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?', '', ' Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive. Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES). The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy. If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions:How will pre-cruise planning be coordinated? (e.g. email, teleconference, workshop)What types of sampling instruments will be deployed on the cruise?How will the cruise event log be recorded? (e.g. the Rolling Deck to Repository (R2R) event logger application, an Excel spreadsheet, or paper logs)Will you prepare a cruise report?', '', ' If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO, along with the project and dataset metadata. Information on how to contribute deployment metadata to BCO-DMO is available on the BCO-DMO website at http://www.bco-dmo.org/how-get-started.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOR2R Scientific Sampling Event LogBCO-DMO DMP Suggestions for Proposals Involving a Research Cruise (PDF)IMBER Data Management CookbookROSCOP (Report of Observations/Samples collected by Oceanographic Programmes) Cruise Summary Form', ' Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available). Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them. It may be useful to group data into four categories:Observational (e.g. in-situ, collected in the field). Examples may include: shipboard underway data; mesozooplankton samples collected by a net system; copepod specimens collected, identified, and preserved; hydrographic casts; alongtrack data; remote sensing (e.g. ocean color); acoustic data.Experimental (e.g. generated in a lab or under controlled conditions). Examples: controlled carbonate chemistry experiments; DNA and RNA sequences.Simulations (e.g. machine-generated). Example: models and their output.Derived (e.g. synthesized from existing datasets). Examples: compiled database, products, reports.If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determined at a later date.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMO The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).Observational Datasets:CTD and Niskin bottle data: CTD data collected using a SeaBird SBE CTD package; processing to be done using SeaBird’s SeaSave software; data will include standard environmental measurements (such as pressure, temperature, salinity, fluorescence). File types: Raw (.con, .hdr, .hex, .bl) and processed and .cnv, .asc, .btl) ASCII files. Repository: BCO-DMOEvent log: Cruise scientific sampling event log; will include event numbers, start/end dates, times & locations of instrument deployments. Will be recorded using the R2R event logger (if available) and on paper log sheets. File types: Excel file converted to .csv; scanned PDFs. Repository: BCO-DMO and Rolling Deck to Repository (R2R).Cruise underway data: Routine underway data collected along the ship’s track (including meteorological data, sea surface temperature, salinity, fluorescence, ADCP). Will be collected by the shipboard instrumentation. File types: .csv ASCII files. Repository: BCO-DMO and R2R.Zooplankton sampling logs and images: Zooplankton will be sampled via Reeve net trawls and MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System) tows during the cruise. Species identified, tow numbers, locations, depths, dates, and times will be recorded by hand on log sheets. Information from log will be transferred into an Excel spreadsheet. Photographs of each tow/trawl will be taken on the ship using a digital camera. File types: PDF files of scanned log sheets; Excel files of sampling logs; images (.jpg files). Repository: BCO-DMO.Experimental Datasets:Pteropod respiration: Physiological experiments carried out on pteropods captured at sea raised under controlled pCO2 conditions; dataset will include data on the experimental treatments and the observed respiration rates. Animals will be captured using a Reeve Net or MOCNESS. Experiments will be conducted in the ship’s lab. File types: Excel file(s). Repository: BCO-DMO.Genetic sequencing: mRNA and DNA sequences from animals collected at sea. Sequencing will be performed at the PI’s lab in Woods Hole, MA following the research cruise. File types: Short-read archive (.sra) and .fasta files. Repository: NCBI; accession numbers to be provided to BCO-DMO.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2254, 230, 1278, 2923, ' Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions:Which file formats will be used to store your data?What type of contextual details (metadata) will you document and how?Are there specific data or metadata standards that you will be adhering to?Will you be using or creating a data dictionary, code list, or glossary?What types of quality control will be used? How will data quality be assessed and flagged?', '', ' Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOBCO-DMO Guidance on Organizing Data in a Spreadsheet', ' Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures. Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following:How will data be shared among project participants during the data collection and analysis phases? (e.g. web page, shared network drive)How/where will data be stored and backed-up?If data volumes will be significant, what is the estimated total file size?', '', ' The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive. Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following:When will data be made publicly available and how? Identify the data repositories you plan to use to make data available.Are the data sensitive in nature (e.g. endangered species concerns, potential patentability)? If so, is public access inappropriate and how will access be provided? (e.g. formal consent agreements, restricted access)Will any permission restrictions (such as an embargo period) need to be placed on the data? If so, what are the reasons and what is the duration of the embargo?Who holds intellectual property rights to the data and how might this affect data access?Who is likely to be interested in re-using the data? What are the foreseeable re-uses of the data?', '', ' Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.Data Sharing via BCO-DMOIf the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.Genomic Data and Other Specialized RepositoriesProvisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.Underway Shipboard DataAll routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOData Repositories List (created by Integrated Earth Data Applications (IEDA))Terms of Use for Data at BCO-DMOR2R Cruise CatalogCreative Commons License TypesUniversity-National Oceanographic Laboratory System (UNOLS)National Center for Biotechnology Information (NCBI)GenBankLong Term Ecological Research (LTER) Network Data Portal', ' Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO Dataset Metadata submission form. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publically available without restriction once submitted to the public repositories.Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use). Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following:What is your long-term strategy for maintaining, curating, and archiving the data?What archive(s) have you identified as a place to deposit data and other research products?', '', ' R2R will ensure that the original underway measurements are archived permanently at NCEI and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data. Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following:If there are multiple investigators involved, what are the data management responsibilities of each personWho will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?', '', ' Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive. Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, etc). Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data—for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements. Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). If implementing the DMP will incur additional costs to the project this fact should be mentioned in the appropriate section of the plan (for example the cost of setting up and maintaining a web site). Details of the costs must be included in the budget justification in the budget section of the proposal. The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Policies and provisions for re-use, re-distribution, and the production of derivatives. Plans for archiving data, samples, and other research products, and for preservation of access to them. The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Policies and provisions for re-use, re-distribution, and the production of derivatives. Plans for archiving data, samples, and other research products, and for preservation of access to them. The types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. The standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Policies and provisions for re-use, re-distribution, and the production of derivatives. Plans for archiving data, samples, and other research products, and for preservation of access to them. Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, VO-compliant tables, XML files, etc.). Include a description of the metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided. "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period of time the web site or data base is expected to be maintained. Note that data taken at national or private observatories may be accessible through public archives (perhaps after a standard proprietary period). Various forms of data (e.g.FITS image and tables, other data tables) also may be deposted with published articles in the AAS journals and other journals. Particular attention should be paid to data sets that are products of well-defined surveys. Also describe your practice before or after formal publication."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your polies for data sharing, including where applicable provisions for protection of privacy, confidentiality, intellectual propoerty, national security, or other rights or requirements. Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.) Describe the standards to be used for all the data types anticipated, including data or file format and metadata. Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project). Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends. Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights. Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education. Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?) Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, etc). Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases. If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data—for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements. Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). If implementing the DMP will incur additional costs to the project this fact should be mentioned in the appropriate section of the plan (for example the cost of setting up and maintaining a web site). Details of the costs must be included in the budget justification in the budget section of the proposal. Specify the roles and responsibilities of all parties with respect to the DMP activities. Specify the types of data or products that will be generated (e.g., test scores, survey responses, images, data tables, video or audio data, sftware, curricular or exhibit materials). Specify how data or products are to be stored, preserved, and shared. Specify any restrictions on data or product storage, access, preservation, or sharing Specify what data formats will be used (e.g., XML files, websites, image files, data tables, software code, text documents, physical materials). Specify how long access to data and products, and sharing of data or products, will be maintained after the life of the project, and how any associated costs will be covered and by whom. If data or products are to be preserved by a third party, please refer to their preservation plans if available. More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans. Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. NSF-PHY Advice to PIs on Data Management Plans Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. NSF-PHY Advice to PIs on Data Management Plans Physics Division PIs should include in their Data Management Plan those aspects of data retention and sharing that would allow them to respond to a question about a published result. Members of formal collaborations may refer to the collaboration\'s existing policies and practices. The DMP should clearly articulate how "sharing of primary data" is to be implemented. It should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It must also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution. Any costs should be explained in the Budget Justification pages. The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained. The DMP should describe the period of data retention. Minimum data retention of research data is three years after conclusion of the award or three years after public release, whichever is later. The DMP should describe the specific data formats, media, and dissemination approaches that will be used to make data available to others, including any metadata. Policies for public access and sharing should be described, including provisions for appropirate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements.Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. Publication delay policies (if applicable) must be clearly stated. Investigators are expected to submit significant findings for publications quickly that are consistent with the publication delay obligations of key partners, such as industrial members of a research center. The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. In collaborative proposals or proposals involving sub-awards, the lead PI is responsible for assuring data storage and access. Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. The Data Management Plan should describe the types of data, metadata, scripts used to generate the data or metadata, experimental results, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project. The Data Management Plan should address the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). The Data Management Plan should address the physical and/or cyber resources and facilities (including those supplied by third parties) that will be used to store and preserve the data after the grant ends. The Data Management Plan should address the policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. The DMP should address the policies and provision for re-use, re-distribution, and the production of derivatives. The DMP should address the plans for archiving data, samples, and other research products, and for the preservation of access to them after the award ends. The DMP should address the plans for archiving data, samples, and other research products, and for the preservation of access to them after the award ends. The Data Management Plan should address the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project) after the grant ends. Describe the types of data (including metadata and annotations, primary or analyzed) and products that will be generated by the research, for example description of samples, numerical data on chemical systems such as spectra, chemical and physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, experimental protocols, algorith specifications, database schemas and data tables, data produced by simulations and software. Data and products generated from Broader Impact activities, such as educational materials, participant information, tutorials and other web-based materials, as well as assessment results, should also be included in the DMP.You may request funds to cover costs of publication, page charges, or preparation of data as a direct cost in your budget proposal, which is evaluated as part of the merit review process. Any costs associated with implementing the DMP should be explained in the Budget Justification. Describe the format and media in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally-accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies to providing data in an accessible format should be provided with minimal added cost. "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases or software repositories (e.g., NMRShiftDB, the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database and Github). For software or code developed as part of the project, include a description of how users can access the code (e.g. licensing, open source) and specific details of the hosting, distribution and dissemination plans. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Note as well any anticipated inclusion of your data in databases that mine the published literature (e.g. PubChem, NIST Chemistry WebBook). Consider using the Digital Object Identifiers (DOI) assignment mechanism not just for journal articles, but for suitably-archived, publishable data sets."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. Discussion on the compliance with the NSFs Public Access Policy is also encouraged. Describe your policies regarding the use of data provided via general access or sharing. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should be defined. For example, if you plan to provide data and images on your website, will the website contain disclaimers or conditions regarding the use of the data in other publications or products? Describe when the data should be archived, how data will be archived, and how preservation of access will be handled. Are there provisions for data backup? Will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? What are the physical and cyber resources and facilities that will be used for data preservation and storage? Will there be an easily accessible index that douments where all archived data are stored and how they can be accessed? What are the roles and responsibilities of all parties with respect to the management and archiving of the data after the grant ends? How long will the data be maintained after the grant ends?CHE-supported large research centers or other programs may specify more stringent data storage, sharing and archiving procedures for research conducted under their awards. Such requirements will be specified in the program solicitation and award conditions. The DMP should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It should also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution or project. The Data Management Plan should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained. SBE is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their DMP statement. The Data Management Plan should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. The Data Management Plan should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories. More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans. Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES). The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy. If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions:How will pre-cruise planning be coordinated? (e.g. email, teleconference, workshop)What types of sampling instruments will be deployed on the cruise?How will the cruise event log be recorded? (e.g. the Rolling Deck to Repository (R2R) event logger application, an Excel spreadsheet, or paper logs)Will you prepare a cruise report?', '', ' If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO, along with the project and dataset metadata. Information on how to contribute deployment metadata to BCO-DMO is available on the BCO-DMO website at http://www.bco-dmo.org/how-get-started.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOR2R Scientific Sampling Event LogBCO-DMO DMP Suggestions for Proposals Involving a Research Cruise (PDF)IMBER Data Management CookbookROSCOP (Report of Observations/Samples collected by Oceanographic Programmes) Cruise Summary Form', ' Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available). Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them. It may be useful to group data into four categories:Observational (e.g. in-situ, collected in the field). Examples may include: shipboard underway data; mesozooplankton samples collected by a net system; copepod specimens collected, identified, and preserved; hydrographic casts; alongtrack data; remote sensing (e.g. ocean color); acoustic data.Experimental (e.g. generated in a lab or under controlled conditions). Examples: controlled carbonate chemistry experiments; DNA and RNA sequences.Simulations (e.g. machine-generated). Example: models and their output.Derived (e.g. synthesized from existing datasets). Examples: compiled database, products, reports.If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determined at a later date.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMO The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).Observational Datasets:CTD and Niskin bottle data: CTD data collected using a SeaBird SBE CTD package; processing to be done using SeaBird’s SeaSave software; data will include standard environmental measurements (such as pressure, temperature, salinity, fluorescence). File types: Raw (.con, .hdr, .hex, .bl) and processed and .cnv, .asc, .btl) ASCII files. Repository: BCO-DMOEvent log: Cruise scientific sampling event log; will include event numbers, start/end dates, times & locations of instrument deployments. Will be recorded using the R2R event logger (if available) and on paper log sheets. File types: Excel file converted to .csv; scanned PDFs. Repository: BCO-DMO and Rolling Deck to Repository (R2R).Cruise underway data: Routine underway data collected along the ship’s track (including meteorological data, sea surface temperature, salinity, fluorescence, ADCP). Will be collected by the shipboard instrumentation. File types: .csv ASCII files. Repository: BCO-DMO and R2R.Zooplankton sampling logs and images: Zooplankton will be sampled via Reeve net trawls and MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System) tows during the cruise. Species identified, tow numbers, locations, depths, dates, and times will be recorded by hand on log sheets. Information from log will be transferred into an Excel spreadsheet. Photographs of each tow/trawl will be taken on the ship using a digital camera. File types: PDF files of scanned log sheets; Excel files of sampling logs; images (.jpg files). Repository: BCO-DMO.Experimental Datasets:Pteropod respiration: Physiological experiments carried out on pteropods captured at sea raised under controlled pCO2 conditions; dataset will include data on the experimental treatments and the observed respiration rates. Animals will be captured using a Reeve Net or MOCNESS. Experiments will be conducted in the ship’s lab. File types: Excel file(s). Repository: BCO-DMO.Genetic sequencing: mRNA and DNA sequences from animals collected at sea. Sequencing will be performed at the PI’s lab in Woods Hole, MA following the research cruise. File types: Short-read archive (.sra) and .fasta files. Repository: NCBI; accession numbers to be provided to BCO-DMO.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (2922, 287, 1745, 2923, ' Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions:Which file formats will be used to store your data?What type of contextual details (metadata) will you document and how?Are there specific data or metadata standards that you will be adhering to?Will you be using or creating a data dictionary, code list, or glossary?What types of quality control will be used? How will data quality be assessed and flagged?', '', ' Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOBCO-DMO Guidance on Organizing Data in a Spreadsheet', ' Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures. Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following:How will data be shared among project participants during the data collection and analysis phases? (e.g. web page, shared network drive)How/where will data be stored and backed-up?If data volumes will be significant, what is the estimated total file size?', '', ' The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive. Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following:When will data be made publicly available and how? Identify the data repositories you plan to use to make data available.Are the data sensitive in nature (e.g. endangered species concerns, potential patentability)? If so, is public access inappropriate and how will access be provided? (e.g. formal consent agreements, restricted access)Will any permission restrictions (such as an embargo period) need to be placed on the data? If so, what are the reasons and what is the duration of the embargo?Who holds intellectual property rights to the data and how might this affect data access?Who is likely to be interested in re-using the data? What are the foreseeable re-uses of the data?', '', ' Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.Data Sharing via BCO-DMOIf the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.Genomic Data and Other Specialized RepositoriesProvisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.Underway Shipboard DataAll routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessBCO-DMO Data Management Best Practices Guide (PDF)How to Get Started Contributing Data to BCO-DMOFrequently Asked Questions (FAQs) about BCO-DMOData Repositories List (created by Integrated Earth Data Applications (IEDA))Terms of Use for Data at BCO-DMOR2R Cruise CatalogCreative Commons License TypesUniversity-National Oceanographic Laboratory System (UNOLS)National Center for Biotechnology Information (NCBI)GenBankLong Term Ecological Research (LTER) Network Data Portal', ' Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO Dataset Metadata submission form. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publically available without restriction once submitted to the public repositories.Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use). Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following:What is your long-term strategy for maintaining, curating, and archiving the data?What archive(s) have you identified as a place to deposit data and other research products?', '', ' R2R will ensure that the original underway measurements are archived permanently at NCEI and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data. Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following:If there are multiple investigators involved, what are the data management responsibilities of each personWho will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?', '', ' Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive. Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, existence of metadata, etc). Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases, and the mechanism for making the existence of an archive publicly known (e.g. by indicating the data sharing mechanism in publications that recognize NSF support). If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data – for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements. Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). If implementing the DMP will incur additional costs to the project this fact should be mentioned in the appropriate section of the plan (for example the cost of setting up and maintaining a web site). Details of the costs must be included in the budget justification in the budget section of the proposal. What types of data, samples, collections, software, materials, etc. will be produced during your project? The project will collect and record <enter data types here (e.g. conductivity, temperature, and depth data or microbial community data)> over the course of the grant. These data include variables such as <enter variables here (e.g. temperature measured in degrees Kelvin or Operational Taxonomic Unit abundance measured in counts)>. Additional data products this research will make available include <list any physical samples, software, model outputs, educational materials, etc.> What types of data, samples, collections, software, materials, etc. will be produced during your project? The project will collect and record <enter data types here (e.g. conductivity, temperature, and depth data or microbial community data)> over the course of the grant. These data include variables such as <enter variables here (e.g. temperature measured in degrees Kelvin or Operational Taxonomic Unit abundance measured in counts)>. Additional data products this research will make available include <list any physical samples, software, model outputs, educational materials, etc.> What will be the approximate number and size of data files that will be produced during your project? There will be aproximately <____> files, each no larger than <___> <MB, GB, TB, other>, for a total storage size of approximately <___>. What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The ADC stores metadata using the Ecological Metadata Language (EML). The ADC does not require users to submit metadata in an EML format. When submiting to the ADC through the website, submiters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submiters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (amoung other information) when applicable.Descriptions of field and laboratory sampling times and locationsDescriptions of field and laboratory sample collection methods Descriptions of field and laboratory sample processing methodsDescriptions of any hardware and software used (including make, model, and version where applicable)Sampling unitsQuality control proceeduresExplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record the following:Descriptions of field and laboratory sampling times and locationsDescriptions of field and laboratory sample collection methods Descriptions of field and laboratory sample processing methodsDescriptions of any hardware and software used (including make, model, and version where applicable)Sampling unitsQuality control proceeduresExplanations for why the particular components detailed above were chosen for this project', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3135, 302, 1901, 961, ' What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The ADC primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the ADC, include in your answer your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the ADC. If you anticipate any data will not be able to be transformed into an open-source format, please provide a reasoning. Data will be collected from <study area> in <enter data formats here (e.g. handwritten lab notebooks, Microsoft Excel files, R scripts)>. All data will be transferred to CSV files for processing and storage. What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The ADC primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the ADC, include in your answer your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the ADC. If you anticipate any data will not be able to be transformed into an open-source format, please provide a reasoning. Data will be collected from <study area> in <enter data formats here (e.g. handwritten lab notebooks, Microsoft Excel files, R scripts)>. All data will be transferred to CSV files for processing and storage. 1. What parties and individuals will be involved with data management in this project? Arctic Data Center Identification Policy: The ADC utilizes ORCiDs (https://orcid.org/) to identify idividuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submiting to the ADC. The following organizations and individuals will be involved with data management in this project <___>. Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements for Arctic Sciences. We <intend, do not intend> to impose a data embargo with the exception of <___> as approved by <the ARC Progam Manager or other NSF unit>. We <expect, do not expect> that the data we generate will require special arrangements due to ethical restrictions or release of indigenous knowledge. There are <restrictions, no restrictions> on the use of data and products created by this project as long as the user includes a citation for the product. There are <privacy concerns, no privacy concerns> associated with the data. Existing data <will, will not> be required for our analysis. These data include <___> and will be obtained from <list website, researcher>. Relevant data will also be made available through these channels: <___>. How will data be accessed and shared during the course of the project? Data files will be stored on a local network. Team members will upload and share files through this network. How will you make your data and other products accessible to others? Arctic Data Center Publication Policy: The ADC provides a long-lived and publically accesible system that is free for users to obtain data and metadata files. Complete submissions to the ADC meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The ADC publically releases datasets once all metadata files, full data sets, and derived data products have been submited and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assit with attribution and discovery.NSF Office of Polar Programs Guidelines The project will upload data files and documentation to the NSF Arctic Data Center <describe when data will be released e.g.: as soon as data have been quality controlled and processed, annually, upon completion of the project>. The data and associated files will be released through the NSF Arctic Data Center. Data and data products will be made available with as few restrictions as possible. These data and metadata will be made freely available for access and use by all via web-based distribution through the NSF Arctic Data Center. When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines How do you anticipate the data for this project will be used? Consider the following: Integration and re-use of the data relies on the data being well-organized and adequately documented. The shared data are expected to be of interest to <list audience(s)>. It is possible that scientists from related disciplines will also use the data. To facilitiate tracking of re-use and to give fair credit to the project and investigators, the NSF Arctic Data Center will provide a recommended formal citation, including a persistent identifier or digital object identifier (DOI) for the submited data set(s). Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. What is the long-term strategy for maintaining, curating, and archiving the data? Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind-down plan', ' <Projects data manager> will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. We will use the NSF Arctic Data Center tools to create metadata for long-term data preservation. Data will be described in accordance with the NSF Arctic Data Center standards. What types of data, samples, collections, software, materials, etc. will be produced during your project? The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What will be the approximate number and size of data files that will be produced during your project? There will be approximately __________ files. What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record the following:descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3214, 306, 1945, 962, ' What types of data, samples, collections, software, materials, etc. will be produced during your project? The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. 1. What parties and individuals will be involved with data management in this project? Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) How will data be accessed and shared during the course of the project? Project files will be stored __________. (Examples are on a local network, in a Git repository, etc.) How will you share and provide access to your data and other products to the general public? Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publically accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.NSF Office of Polar Programs Guidelines When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines How do you anticipate the data for this project will be used? Consider the following: __________ data are expected to be used by __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify usage expectations for each type of data detailed in your description of data.) Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. What is the long-term strategy for maintaining, curating, and archiving the data? Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind down plan', ' The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. What types of data, samples, collections, software, materials, etc. will be produced during your project? The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What will be the approximate number and size of data files that will be produced during your project? There will be approximately __________ files. What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record the following:descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3244, 310, 1962, 962, ' What types of data, samples, collections, software, materials, etc. will be produced during your project? The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. 1. What parties and individuals will be involved with data management in this project? Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) How will data be accessed and shared during the course of the project? Project files will be stored __________. (Examples are on a local network, in a Git repository, etc.) How will you share and provide access to your data and other products to the general public? Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publically accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.NSF Office of Polar Programs Guidelines When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines How do you anticipate the data for this project will be used? Consider the following: __________ data are expected to be used by __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify usage expectations for each type of data detailed in your description of data.) Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. What is the long-term strategy for maintaining, curating, and archiving the data? Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind down plan', ' The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What will be the approximate number and size of data files that will be produced during your project? There will be approximately __________ files. The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record the following:descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3262, 311, 1971, 961, ' What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. 1. What parties and individuals will be involved with data management in this project? Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) How will data be accessed and shared during the course of the project? Project files will be stored __________. (Examples are on a local network, in a Git repository, etc.) How will you share and provide access to your data and other products to the general public? Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publically accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.NSF Office of Polar Programs Guidelines When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines How do you anticipate the data for this project will be used? Consider the following: __________ data are expected to be used by __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify usage expectations for each type of data detailed in your description of data.) Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. What is the long-term strategy for maintaining, curating, and archiving the data? Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind down plan', ' The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What will be the approximate number and size of data files that will be produced during your project? There will be approximately __________ files. What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record the following:descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3296, 315, 1993, 962, ' The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. What format(s) will data and metadata be collected, processed, and stored in? Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. 1. What parties and individuals will be involved with data management in this project? Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) How will data be accessed and shared during the course of the project? Project files will be stored __________. (Examples are on a local network, in a Git repository, etc.) How will you share and provide access to your data and other products to the general public? Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publically accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.NSF Office of Polar Programs Guidelines When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines How do you anticipate the data for this project will be used? Consider the following: __________ data are expected to be used by __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify usage expectations for each type of data detailed in your description of data.) Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. What is the long-term strategy for maintaining, curating, and archiving the data? Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind down plan', ' The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) What will be the approximate number and size of data files that will be produced during your project? There will be approximately __________ files. What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record the following:descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceeduresexplanations for why the particular components detailed above were chosen for this project', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3311, 316, 2001, 962, ' The researchers will collect and record __________. (Enter data types here. Examples are conductivity, temperature, and depth (CTD) data, gas flux data, aerial photos, modeled atmospheric data, etc.) Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. __________ data are expected to need provisions for __________. (Examples are appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Make sure to specify all the types of data that are expected to need provisions.) How will data be accessed and shared during the course of the project? Project files will be stored __________. (Examples are on a local network, in a Git repository, etc.) How will you share and provide access to your data and other products to the general public? Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publically accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.NSF Office of Polar Programs Guidelines When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines __________ data are expected to be used by __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify usage expectations for each type of data detailed in your description of data.) Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind down plan', ' The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. Arctic Data Center Identification Policy: The Arctic Data Center utilizes ORCiDs (https://orcid.org/) to identify individuals associated with each dataset. An ORCiD will be required for the primary contact of each dataset. ORCiDs are not required for all associated parties but are encouraged so that proper identification and attribution can be given. Please plan on creating (when necessary) and recording ORCiDs for each individual involved with your project before submitting to the Arctic Data Center. The purpose of this section is to ensure that the individuals ultimately responsible for ensuring compliance with the data management plan are both aware and agree to their roles. The project’s principal investigator, Jane Doe, will ultimately be responsible for all of the data management. It is Doe’s responsibility to make sure all of the project team members are taught the proper data management skills and uphold the data management requirements. Doe will delegate data management duties to the laboratory project data manager, Bonnie, along with graduate student, Clyde, working in the field. The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project. This is the most detailed section of the data management plan. Describe the categories of data being collected and how they tie into the data associated with the methods used to collect that data. Expect this section to be the most detailed section, taking up a large portion of your data management plan document. During this project, soil cores will be collected from three sites representing varying degrees of snow accumulation. Temperature, moisture and active layer thaw depth will be collected to record soil physical properties. Soil samples from each core will be analyzed for carbon concentration, nitrogen concentration and pH.Aerial photos of each of the three sites will also be taken twice annually to visualize the snow cover. Additional data products that will be made available include data analysis codes in R and high school-level educational materials regarding soil properties in changing climatic conditions in the Arctic. This is the most detailed section of the data management plan. Describe the categories of data being collected and how they tie into the data associated with the methods used to collect that data. Expect this section to be the most detailed section, taking up a large portion of your data management plan document. During this project, soil cores will be collected from three sites representing varying degrees of snow accumulation. Temperature, moisture and active layer thaw depth will be collected to record soil physical properties. Soil samples from each core will be analyzed for carbon concentration, nitrogen concentration and pH.Aerial photos of each of the three sites will also be taken twice annually to visualize the snow cover. Additional data products that will be made available include data analysis codes in R and high school-level educational materials regarding soil properties in changing climatic conditions in the Arctic. What will be the approximate number and size of data files that will be produced during your project? In this project, there will be six experimental treatments applied to the Saxifraga cespitosa plants, with four replicates for each treatment collected three times during the year. Therefore, there will be approximately 72 data files each year (6 treatments x 4 replicates x 3 collections per year). The 72 data files will be approximately 720 MB in size. What type of metadata (information others might need to use your data) will be collected during your project? Arctic Data Center Metadata Policy: The Arctic Data Center stores metadata using the Ecological Metadata Language (EML). The Arctic Data Center does not require users to submit metadata in an EML format. When submitting to the Arctic Data Center through the website, submitters can submit plain text descriptions of their data which will be automattically transformed into an EML format for archiving. That being said, submitters should have complete plain text records of the metadata associated with their project. Complete metadata records should contain the following information (among other information) when applicable.descriptions of field and laboratory sampling times and locationsdescriptions of field and laboratory sample collection methods descriptions of field and laboratory sample processing methodsdescriptions of any hardware and software used (including make, model, and version where applicable)sampling unitsquality control proceduresexplanations for why the particular components detailed above were chosen for this project', ' The project will collect and record a description of the time of soil core collection in the field, along with the time of soil core processing in the laboratory. The exact locations and conditions of the field sites will be described as well as the laboratory conditions and location of soil sample analysis. A detailed description of the soil core sample collection and processing methods in the field, as well as the laboratory soil carbon and nitrogen concentration collection and processing methods will be included. Units will be recorded for all samples. Soil carbon and nitrogen will be reported in %C and %N, respectively, along with the C:N ratio and the %delta 13C and %delta 15N. Soil depth will be recorded in centimeters. Quality control procedures will be followed in both the field and the laboratory during sample collection and processing, and the details of these procedures will be included. The decisions for the inclusion of each component of the project, including the specific sampling methods, units, and procedures, will be provided. The hardware and software used will be provided. R Studio will be used for coding and data analysis, with the code shared in a Github repository. Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. Additionally, please provide ORCiD identification for all individuals collecting and analyzing the data for proper citation and credit. The local and traditional knowledge data will be collected during interviews using tape recording devices. The survey answers will then be transcribed and exported to CSV files for storage. Metadata will be documented in CSV files. The soil core data will be collected by hand in the field and then entered into a CSV file for storage. The soil core metadata will be entered in CSV files along with the metadata. Imagery metadata from the core sites will be encoded in NetCDF files. All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center. Arctic Data Center Data Format Policy: The Arctic Data Center primarily supports the upload of open-source, ubiquitous, and easy-to-read data formats. Examples of such formats are Comma Separated Values (CSV) files, text (TXT) files, PNG, JPEG or TIFF image files, and NetCDF files among many others. If you plan to submit to the Arctic Data Center, include your planned methods to create open-source, ubiquitous, and easy-to-read data. If you plan to work with any proprietary data formats such as Excel workbooks or MATLAB files, please include a plan to transform all data stored in these formats into an open-source format before submission to the Arctic Data Center. If you anticipate any data will not be able to be transformed into an open-source format, please provide your reasoning. Additionally, please provide ORCiD identification for all individuals collecting and analyzing the data for proper citation and credit. The local and traditional knowledge data will be collected during interviews using tape recording devices. The survey answers will then be transcribed and exported to CSV files for storage. Metadata will be documented in CSV files. The soil core data will be collected by hand in the field and then entered into a CSV file for storage. The soil core metadata will be entered in CSV files along with the metadata. Imagery metadata from the core sites will be encoded in NetCDF files. All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center. Arctic Data Center Publication Policy:The Arctic Data Center provides a long-lived and publicly accessible system that is free for users to obtain data and metadata files. Complete submissions to the Arctic Data Center meet the requirements set by the The Office of Polar Programs that require that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive. The Arctic Data Center publically releases datasets once all metadata files, full data sets, and derived data products have been submitted and compiled into a unique dataset. Each dataset will be given a unique Digital Object Identifier (DOI) that will assist with attribution and discovery.NSF Office of Polar Programs Guidelines Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research. Survey data taken during interviews with the local residents are expected to need provisions for confidentiality due to ethical restrictions and the protection of indigenous knowledge. This sensitive data is governed by an Institutional Review Board policy. Additionally, this project deals with endangered species, so similarly sensitive data, particularly location data, will also be exempted from the archiving requirements set for Arctic Sciences research due to confidentiality and species protection. When is the approximate release date of the data products? NSF Office of Polar Programs Guidelines The salmon catch data are expected to be used by other researchers studying Arctic food web systems in addition to government agencies with regard to establishing catch limits in the area. Local fishermen and fish modellers may also make use of this data. The data will be added to a long-term data set to continue to observe changes in the region through time. Will any permission restrictions need to be placed on the data? Consider the following:Who will be allowed to use the data?How will others be allowed to use the data?Will others be allowed to disseminate the data. Arctic Data Center Licensing and Data Distribution Policy: All data and metadata will be released under either the CC-0 Public Domain Dedication or the Creative Commons Attribution 4.0 International License (CC BY), with the potential exception of social science data that have certain sensitivities related to privacy or confidentiality. In cases where legal (e.g., contractual) or ethical (e.g., human subjects) restrictions to data sharing exist, requests to restrict data publication must be requested in advance and in writing and are subject to the approval of NSF, who will ensure compliance with all federal, university, and Institutional Review Board policies on the use of restricted data. All data will be accessible to the public and subject to usage and dissemination restrictions under the CC-0 Public Domain Dedication License. Arctic Data Center Data Preservation Policy: The Arctic Data Center ensures the long-term preservation of the data entrusted to the repository. The guiding principles for the preservation plan follow:Preserve the bitsOpen science, open standardsReplicate data and metadataStrong versioningFrequent auditingA wind down plan', ' The data manager will follow the NSF Arctic Data Center guidelines to provide accurate and complete documentation for data preservation. The NSF Arctic Data Center will ensure that the data are curated in a relevant long-term archive and ensure data will be available after project funding has ended. The Division of Earth Sciences requires that full data sets, derived data products (e.g. model results, output, and workflows), software, and physical collections must be made publicly accessible within two (2) years of final collection. Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures. Policies and provisions for re-use, re-distribution, and the production of derivatives. Plans for archiving data, samples, and other research products, and for preservation of access to them. The DMP should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data. It should also consider changes to roles and responsibilities that will occur should a principal investigator or co-PI leave the institution or project. Any costs should be explained in the Budget Justification pages. The DMP should describe the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project. It should then describe the expected types of data to be retained. SBE is committed to timely and rapid data distribution. However, it recognizes that types of data can vary widely and that acceptable norms also vary by scientific discipline. It is strongly committed, however, to the underlying principle of timely access, and applicants should address how this will be met in their DMP statement. The DMP should describe data formats, media, and dissemination approaches that will be used to make data and metadata available to others. Policies for public access and sharing should be described, including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. Research centers and major partnerships with industry or other user communities must also address how data are to be shared and managed with partners, center members, and other major stakeholders. The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories. More stringent data management requirements may be specified in particular NSF solicitations or result from local policies and best practices at the PI’s home institution. Additional requirements will be specified in the program solicitation and award conditions. Principal Investigators to be supported by such programs must discuss how they will meet these additional requirements in their Data Management Plans. The Data Management Plan should describe the types of data, metadata, scripts used to generate the data or metadata, experimental results, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project. The Data Management Plan should address the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It should also cover any other types of information that would be maintained and shared regarding data, e.g. the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other metadata. The Data Management Plan should address the policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. It should cover any factors that limit the ability to manage and share data, e.g. legal and ethical restrictions on access to human subject data. The Data Management Plan should address the policies and provision for re-use, re-distribution, and the production of derivatives. The Data Management Plan should address the plans for archiving data, samples, and other research products, and for the preservation of access to them. It should cover the period of time the data will be retained and shared; how data are to be managed, maintained, and disseminated; and mechanisms and formats for storing data and making them accessible to others, which may include third party facilities and repositories. The Data Management Plan should clearly articulate how the PI and co-PIs plan to manage and disseminate data generated by the project. The plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data, and consider changes that would occur should a PI or co-PI leave the institution or project. It should describe how the research team plans to deposit data into any relevant and appropriate disciplinary repositories that are appropriately managed and that are likely to maintain the metadata necessary for future use and discovery. Any costs associated with implementing the DMP should be explained in the Budget Justification. Describe the types of data (including metadata and annotations, primary or analyzed) and products that will be generated by the research, for example description of samples, numerical data on chemical systems such as spectra, chemical and physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, experimental protocols, algorith specifications, database schemas and data tables, data produced by simulations and software. Data and products generated from Broader Impact activities, such as educational materials, participant information, tutorials and other web-based materials, as well as assessment results, should also be included in the DMP.You may request funds to cover costs of publication, page charges, or preparation of data as a direct cost in your budget proposal, which is evaluated as part of the merit review process. Any costs associated with implementing the DMP should be explained in the Budget Justification. Describe the format and media in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally-accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies to providing data in an accessible format should be provided with minimal added cost. "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases or software repositories (e.g., NMRShiftDB, the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database and Github). For software or code developed as part of the project, include a description of how users can access the code (e.g. licensing, open source) and specific details of the hosting, distribution and dissemination plans. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Note as well any anticipated inclusion of your data in databases that mine the published literature (e.g. PubChem, NIST Chemistry WebBook). Consider using the Digital Object Identifiers (DOI) assignment mechanism not just for journal articles, but for suitably-archived, publishable data sets."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. Discussion on the compliance with the NSFs Public Access Policy is also encouraged. Describe your policies regarding the use of data provided via general access or sharing. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should be defined. For example, if you plan to provide data and images on your website, will the website contain disclaimers or conditions regarding the use of the data in other publications or products? Describe when the data should be archived, how data will be archived, and how preservation of access will be handled. Are there provisions for data backup? Will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? What are the physical and cyber resources and facilities that will be used for data preservation and storage? Will there be an easily accessible index that douments where all archived data are stored and how they can be accessed? What are the roles and responsibilities of all parties with respect to the management and archiving of the data after the grant ends? How long will the data be maintained after the grant ends?CHE-supported large research centers or other programs may specify more stringent data storage, sharing and archiving procedures for research conducted under their awards. Such requirements will be specified in the program solicitation and award conditions. Describe the types of data, physical samples or collections, software, curriculum materials, and other materials to be produced in the course of the project. (For collaborative proposals, the DMP must cover all the various data types being collected by each collaborator.) Describe the standards to be used for all the data types anticipated, including data or file format and metadata. [Note: Where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies.] Describe the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project). Describe the dissemination methods that will be used to make data and metadata available to others during the period of the award, and any modifications or additional technical information regarding data access after the grant ends. Describe the PI’s policies for data sharing, public access and re-use, including re-distribution by others and the production of derivatives. Where appropriate, include provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights. Where relevant, describe plans for archiving data, samples, software, and other research products, and for on-going access to these products through their lifecycle of usefulness to research and education. Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?) What types of data (experimental, computational, or text-based), metadata, samples, physical collections, models, software, curriculum materials, and other materials will be collected and/or generated in the course of the project? The DMP should describe the expected types of data to be retained, managed, and shared, and the plans for doing so. What descriptions of the metadata are needed to make the actual data products useful and reproducible for the general researcher? For collaborative proposals, the DMP should describe the roles and responsibilities of all parties with respect to the management of data (including contingency plans for the departure of key personnel from the project) both during and after the grant cycle. In what format and/or media will the data or products be stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats)? Where data are stored in unusual or not generally accessible formats, how may the data be converted to more accessible formats or otherwise made available to interested parties? When existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies. In general, solutions and remedies to providing data in an accessible format should be offered with minimal added cost. What specific dissemination approaches will be used to make data available and accessible to others, including any pertinent metadata needed to interpret the data? In this case, "available and accessible" refers to data that can be found and obtained without a personal request to the PI, for example by download from a public repository. What plans, if any, are in place for providing access to data, including websites maintained by the research group and contributions to public databases/repositories? For software or code developed as part of the project, include a description of how users can access the code (e.g., licensing, open source) and specific details of the hosting, distribution and dissemination plans. If maintenance of a website or database is the direct responsibility of the research group, what is the period of time the website or database is expected to be maintained? What are the practices or policies regarding the release of POST-AWARD MANAGEMENT data – for example, are they available before or after formal publication? What is the approximate duration of time that the data will be kept private? “Data sharing” refers to the release of data in response to a specific request from an interested party. What are the policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements? Research centers and major partnerships with industry or other user communities should also address how data are to be shared and managed with partners, center members, and other major stakeholders; publication delay policies (if applicable) should be clearly stated. What are your policies regarding the use of data provided via general access or sharing? For data to be deemed “re-usable,” it must be accompanied by any metadata needed to reproduce the data, e.g., the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other pertinent metadata. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should also be clearly articulated. For example, if you plan to provide data and images on your website, will the website contain disclaimers or condition regarding the use of the data in other publications or products? When and how will data be archived and how will access be preserved over time? For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). Where no data or sample repository exists for collected data or samples, metadata should be prepared and made publicly available over the Internet and the PI should employ alternative strategies for complying with the general philosophy of sharing research products and data as described above What types of data (experimental, computational, or text-based), metadata, samples, physical collections, models, software, curriculum materials, and other materials will be collected and/or generated in the course of the project? The DMP should describe the expected types of data to be retained, managed, and shared, and the plans for doing so. What descriptions of the metadata are needed to make the actual data products useful and reproducible for the general researcher? For collaborative proposals, the DMP should describe the roles and responsibilities of all parties with respect to the management of data (including contingency plans for the departure of key personnel from the project) both during and after the grant cycle. In what format and/or media will the data or products be stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats)? Where data are stored in unusual or not generally accessible formats, how may the data be converted to more accessible formats or otherwise made available to interested parties? When existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies. In general, solutions and remedies to providing data in an accessible format should be offered with minimal added cost. What specific dissemination approaches will be used to make data available and accessible to others, including any pertinent metadata needed to interpret the data? In this case, "available and accessible" refers to data that can be found and obtained without a personal request to the PI, for example by download from a public repository. What plans, if any, are in place for providing access to data, including websites maintained by the research group and contributions to public databases/repositories? For software or code developed as part of the project, include a description of how users can access the code (e.g., licensing, open source) and specific details of the hosting, distribution and dissemination plans. If maintenance of a website or database is the direct responsibility of the research group, what is the period of time the website or database is expected to be maintained? What are the practices or policies regarding the release of POST-AWARD MANAGEMENT data – for example, are they available before or after formal publication? What is the approximate duration of time that the data will be kept private? “Data sharing” refers to the release of data in response to a specific request from an interested party. What are the policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements? Research centers and major partnerships with industry or other user communities should also address how data are to be shared and managed with partners, center members, and other major stakeholders; publication delay policies (if applicable) should be clearly stated. What are your policies regarding the use of data provided via general access or sharing? For data to be deemed “re-usable,” it must be accompanied by any metadata needed to reproduce the data, e.g., the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other pertinent metadata. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should also be clearly articulated. For example, if you plan to provide data and images on your website, will the website contain disclaimers or condition regarding the use of the data in other publications or products? When and how will data be archived and how will access be preserved over time? For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). Where no data or sample repository exists for collected data or samples, metadata should be prepared and made publicly available over the Internet and the PI should employ alternative strategies for complying with the general philosophy of sharing research products and data as described above What types of data (experimental, computational, or text-based), metadata, samples, physical collections, models, software, curriculum materials, and other materials will be collected and/or generated in the course of the project? The DMP should describe the expected types of data to be retained, managed, and shared, and the plans for doing so. What descriptions of the metadata are needed to make the actual data products useful and reproducible for the general researcher? For collaborative proposals, the DMP should describe the roles and responsibilities of all parties with respect to the management of data (including contingency plans for the departure of key personnel from the project) both during and after the grant cycle. In what format and/or media will the data or products be stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats)? Where data are stored in unusual or not generally accessible formats, how may the data be converted to more accessible formats or otherwise made available to interested parties? When existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies. In general, solutions and remedies to providing data in an accessible format should be offered with minimal added cost. What specific dissemination approaches will be used to make data available and accessible to others, including any pertinent metadata needed to interpret the data? In this case, "available and accessible" refers to data that can be found and obtained without a personal request to the PI, for example by download from a public repository. What plans, if any, are in place for providing access to data, including websites maintained by the research group and contributions to public databases/repositories? For software or code developed as part of the project, include a description of how users can access the code (e.g., licensing, open source) and specific details of the hosting, distribution and dissemination plans. If maintenance of a website or database is the direct responsibility of the research group, what is the period of time the website or database is expected to be maintained? What are the practices or policies regarding the release of POST-AWARD MANAGEMENT data – for example, are they available before or after formal publication? What is the approximate duration of time that the data will be kept private? “Data sharing” refers to the release of data in response to a specific request from an interested party. What are the policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements? Research centers and major partnerships with industry or other user communities should also address how data are to be shared and managed with partners, center members, and other major stakeholders; publication delay policies (if applicable) should be clearly stated. What are your policies regarding the use of data provided via general access or sharing? For data to be deemed “re-usable,” it must be accompanied by any metadata needed to reproduce the data, e.g., the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other pertinent metadata. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should also be clearly articulated. For example, if you plan to provide data and images on your website, will the website contain disclaimers or condition regarding the use of the data in other publications or products? When and how will data be archived and how will access be preserved over time? For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available). Where no data or sample repository exists for collected data or samples, metadata should be prepared and made publicly available over the Internet and the PI should employ alternative strategies for complying with the general philosophy of sharing research products and data as described above Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, VO-compliant tables, XML files, etc.). Include a description of the metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided. "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period of time the web site or data base is expected to be maintained. Note that data taken at national or private observatories may be accessible through public archives (perhaps after a standard proprietary period). Various forms of data (e.g.FITS image and tables, other data tables) also may be deposted with published articles in the AAS journals and other journals. Particular attention should be paid to data sets that are products of well-defined surveys. Also describe your practice before or after formal publication."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your polies for data sharing, including where applicable provisions for protection of privacy, confidentiality, intellectual propoerty, national security, or other rights or requirements. Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself. Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators. A grantee or investigator also may request a particular adjustment or exception from the cognizant NSF Program Officer. Investigators and grantees are encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable. NSF normally allows grantees to retain principal legal rights to intellectual property developed under NSF grants to provide incentives for development and dissemination of inventions, software and publications that can enhance their usefulness, accessibility and upkeep. Such incentives do not, however, reduce the responsibility that investigators and organizations have as members of the scientific and engineering community, to make results, data and collections available to other researchers. NSF program management will implement these policies for dissemination and sharing of research results, in ways appropriate to field and circumstances, through the proposal review process; through award negotiations and conditions; and through appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like. The Division of Earth Sciences requires that full data sets, derived data products (e.g. model results, output, and workflows), software, and physical collections must be made publicly accessible within two (2) years of final collection. Standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It is the responsibility of researchers and organizations to make results, data, derived data products, and collections available to the research community in a timely manner and at a reasonable cost. In the interest of full and open access, data should be provided at the lowest possible cost to researchers and educators. This cost should, as a first principle, be no more than the marginal cost of filling a specific user request. Data may be made available for secondary use through submission to a national data center, publication in a widely available scientific journal, book or website, through the institutional archives that are standard for a particular discipline (e.g. IRIS for seismological data, UNAVCO for GP data), or through other EAR-specified repositories. Data inventories should be published or entered into a public database periodically and when there is a significant change in type, location or frequency of such observations. Principal Investigators working in coordinated programs may establish (in consultation with other funding agencies and NSF) more stringent data submission procedures. Policies and provisions for re-use, re-distribution, and the production of derivatives. Plans for archiving data, samples, and other research products, and for preservation of access to them. Identify any published data policies with which the project will comply, including the NSF OCE Data and Sample Policy as well as other policies that may be relevant if the project is part of a large coordinated research program (e.g. GEOTRACES). The project investigators will comply with the data management and dissemination policies described in the NSF Award and Administration Guide (AAG, Chapter VI.D.4) and the NSF Division of Ocean Sciences Sample and Data Policy. If the proposed project involves a research cruise, describe the cruise plans. (Skip this section if it is not relevant to your proposal.) Consider the following questions:How will pre-cruise planning be coordinated? (e.g. email, teleconference, workshop)What types of sampling instruments will be deployed on the cruise?How will the cruise event log be recorded? (e.g. the Rolling Deck to Repository (R2R) event logger application, an Excel spreadsheet, or paper logs)Will you prepare a cruise report?', '', ' If cruise plans are not known at this time, it is appropriate to omit this section or to state that cruise plans will be made at a later date. Funded projects that involve deployments (including research cruises as well as deployments of moorings, floats, and gliders) will be expected to provide deployment metadata to BCO-DMO, along with the project and dataset metadata. Information on how to contribute deployment metadata to BCO-DMO is available on the BCO-DMO website at http://www.bco-dmo.org/how-get-started.BCO-DMO Quick Start Guide (PDF)University-National Oceanographic Laboratory System (UNOLS)NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessHow to Get Started Contributing Data to BCO-DMOR2R Scientific Sampling Event Log', ' Pre-cruise planning will be done via teleconferencing and a planning workshop. Detailed plans for station locations, instrument deployment, water sampling strategy, and water sample allocation will be written up as a science implementation plan for the cruise. The actual sampling events will be recorded on paper logs (scanned into PDF documents) and/or in a digital event log using the R2R event logger application (if available). Provide a description of the types of data to be produced during the project. Identify the types of data, samples, physical collections, software, derived models, curriculum materials, and other materials to be produced in the course of the project. Include a description of the location of collection, collection methods and instruments, expected dates or duration of collection. If you will be using existing datasets, state this and include how you will obtain them. It may be useful to group data into four categories:Observational (e.g. in-situ, collected in the field). Examples may include: shipboard underway data; mesozooplankton samples collected by a net system; copepod specimens collected, identified, and preserved; hydrographic casts; alongtrack data; remote sensing (e.g. ocean color); acoustic data.Experimental (e.g. generated in a lab or under controlled conditions). Examples: controlled carbonate chemistry experiments; DNA and RNA sequences.Simulations (e.g. machine-generated). Example: models and their output.Derived (e.g. synthesized from existing datasets). Examples: compiled database, products, reports.If the expected dates or duration of collection are not known at this time (e.g. due to funding schedules or ship availability), it is appropriate to give approximations, the ideal dates/duration, or to state that these details will be determined at a later date.BCO-DMO Quick Start Guide (PDF)NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessHow to Get Started Contributing Data to BCO-DMO', ' The project will produce several observational and experimental datasets, described in the list below. In addition to the datasets described below, educational resources produced by the project, including data and images, will be made available for public use on the COSEE.net website. Observational data will be collected on a North Atlantic research cruise planned to take place during the summer months (July-August).Observational Datasets:CTD and Niskin bottle data: CTD data collected using a SeaBird SBE CTD package; processing to be done using SeaBird’s SeaSave software; data will include standard environmental measurements (such as pressure, temperature, salinity, fluorescence). File types: Raw (.con, .hdr, .hex, .bl) and processed and .cnv, .asc, .btl) ASCII files. Repository: BCO-DMOEvent log: Cruise scientific sampling event log; will include event numbers, start/end dates, times & locations of instrument deployments. Will be recorded using the R2R event logger (if available) and on paper log sheets. File types: Excel file converted to .csv; scanned PDFs. Repository: BCO-DMO and Rolling Deck to Repository (R2R).Cruise underway data: Routine underway data collected along the ship’s track (including meteorological data, sea surface temperature, salinity, fluorescence, ADCP). Will be collected by the shipboard instrumentation. File types: .csv ASCII files. Repository: BCO-DMO and R2R.Zooplankton sampling logs and images: Zooplankton will be sampled via Reeve net trawls and MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System) tows during the cruise. Species identified, tow numbers, locations, depths, dates, and times will be recorded by hand on log sheets. Information from log will be transferred into an Excel spreadsheet. Photographs of each tow/trawl will be taken on the ship using a digital camera. File types: PDF files of scanned log sheets; Excel files of sampling logs; images (.jpg files). Repository: BCO-DMO.Experimental Datasets:Pteropod respiration: Physiological experiments carried out on pteropods captured at sea raised under controlled pCO2 conditions; dataset will include data on the experimental treatments and the observed respiration rates. Animals will be captured using a Reeve Net or MOCNESS. Experiments will be conducted in the ship’s lab. File types: Excel file(s). Repository: BCO-DMO.Genetic sequencing: mRNA and DNA sequences from animals collected at sea. Sequencing will be performed at the PI’s lab in Woods Hole, MA following the research cruise. File types: Short-read archive (.sra) and .fasta files. Repository: NCBI; accession numbers to be provided to BCO-DMO.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5106, 468, 2960, 2923, ' Identify the formats and standards to be used for data and metadata formatting and content. Where existing standards are absent or deemed inadequate, these formats and contents should be documented along with any proposed solutions or remedies. Consider the following questions:Which file formats will be used to store your data?What type of contextual details (metadata) will you document and how?Are there specific data or metadata standards that you will be adhering to?Will you be using or creating a data dictionary, code list, or glossary?What types of quality control will be used? How will data quality be assessed and flagged?', '', ' Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses.BCO-DMO Quick Start Guide (PDF)NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessHow to Get Started Contributing Data to BCO-DMO', ' Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures. Describe how project data will be stored, accessed, and shared among project participants during the course of the project. Consider the following:How will data be shared among project participants during the data collection and analysis phases? (e.g. web page, shared network drive)How/where will data be stored and backed-up?If data volumes will be significant, what is the estimated total file size?', '', ' The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive. Describe mechanisms for data access and sharing, and describe any related policies and provisions for re-use, re-distribution, and the production of derivatives. Include provisions for appropriate protections of privacy, confidentiality, security, intellectual property, or other rights or requirements. Consider the following:When will data be made publicly available and how? Identify the data repositories you plan to use to make data available.Are the data sensitive in nature (e.g. endangered species concerns, potential patentability)? If so, is public access inappropriate and how will access be provided? (e.g. formal consent agreements, restricted access)Will any permission restrictions (such as an embargo period) need to be placed on the data? If so, what are the reasons and what is the duration of the embargo?Who holds intellectual property rights to the data and how might this affect data access?Who is likely to be interested in re-using the data? What are the foreseeable re-uses of the data?', '', ' Explain how and when data will be made available. Also describe any re-use and re-distribution policies and how the data sharing plans are related to those policies. Identify who will be allowed to use your data and whether or not they will be allowed to disseminate your data. If access to, use of, or dissemination of data will be restricted, explain how you will codify and communicate these restrictions.Data Sharing via BCO-DMOIf the proposal is being submitted to the NSF Division of Ocean Sciences’ (OCE) Biological or Chemical Oceanography Sections or Division of Polar Programs (PLR) Antarctic Sciences (ANT) Organisms & Ecosystems Program, then the two page plan can state that BCO-DMO staff will work with you to manage the data, and that data or model results generated during the proposed research project will be contributed to the BCO-DMO system. BCO-DMO provides data management services at no additional cost to projects funded by these NSF sections/programs.Project investigators funded by these sections/programs can work with BCO-DMO to make project data available online, in compliance with the NSF OCE Sample and Data Policy. PIs of funded projects will be expected to submit project metadata to BCO-DMO beginning with the award/proposal number and DMP for proposals that are recommended for funding.BCO-DMO can deal with a wide variety of data, including but not limited to biological, chemical, and physical oceanography measurements. BCO-DMO data managers routinely serve in-situ data including standard hydrographic, biogeochemical, biological, ecological, and microbial measurements and chemical tracers; experimental and model results; images and movies, etc. If you are uncertain if BCO-DMO is an appropriate repository for your data, please contact info@bco-dmo.org.See Appendices III and IV of the OCE Sample and Data Policy for information on other suggested databases and repositories for physical samples.Genomic Data and Other Specialized RepositoriesProvisions should be made for the sharing and storage of genetic and molecular data in a publicly accessible, permanent database such as the various NCBI databases (e.g. GenBank), RAST, MG-RAST, etc. Information about the types of data accepted by GenBank is available on their website at http://www.ncbi.nlm.nih.gov/genbank/submit_types. If known, it’d be helpful to disclose the details and availability of bioinformatics pipelines that will be used in next-generation methods. Accommodations for sharing of metagenome, metatranscriptome, and proteomics data should also be described in the DMP.BCO-DMO can enable discovery of data that have been contributed to specialized repositories (e.g. NCBI, LTER data catalog, CDIAC). For example, genetic sequence data are best served by an NCBI repository such as GenBank. Metadata and accession numbers/URLs/unique identifiers can then be provided to BCO-DMO so that access to these alternate repositories can be provided through the BCO-DMO website.Underway Shipboard DataAll routine underway data collected by vessel-resident instrumentation aboard UNOLS-supported oceanographic research vessels will be submitted to the appropriate long-term archive through the Rolling Deck to Repository (R2R) program. The PI is responsible for disseminating the data and metadata produced by the science party’s research.BCO-DMO Quick Start Guide (PDF)NSF Division of Ocean Sciences Sample and Data PolicyNSF Frequently Asked Questions (FAQs) for Public AccessHow to Get Started Contributing Data to BCO-DMOData Repositories List (created by Integrated Earth Data Applications (IEDA))Terms of Use for Data at BCO-DMOR2R Cruise CatalogCreative Commons License TypesNational Center for Biotechnology Information (NCBI)GenBankLong Term Ecological Research (LTER) Network Data Portal', ' Immediately after completion of the research cruise, underway data and metadata will be submitted to the Rolling Deck to Repository (R2R) project. DNA sequences will be deposited in the National Center for Biotechnology Information (NCBI) database GenBank upon submission of manuscripts. GenBank accession numbers will be provided to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) in an Excel spreadsheet or .CSV file and metadata will be provided using the BCO-DMO Dataset Metadata submission form. Data sets produced by the science party will be made available through the BCO-DMO data system within two-years from the date of collection. The project investigators will work with BCO-DMO data managers to make project data available online in compliance with the NSF OCE Sample and Data Policy. Data, samples, and other information collected under this project can be made publically available without restriction once submitted to the public repositories.Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global climate system. We will adhere to and promote the standards, policies, and provisions for data and metadata submission, access, re-use, distribution, and ownership as prescribed by the BCO-DMO Terms of Use (http://www.bco-dmo.org/terms-use). Describe the plans for long-term archiving of data, samples, and other research products, and for preservation of access to them. Consider the following:What is your long-term strategy for maintaining, curating, and archiving the data?What archive(s) have you identified as a place to deposit data and other research products?', '', ' R2R will ensure that the original underway measurements are archived permanently at NCEI and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data. Describe the roles and responsibilities of all parties with respect to the management of the data. Consider the following:If there are multiple investigators involved, what are the data management responsibilities of each personWho will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?', '', ' Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive. Describe the types of data and products that will be generated in the research, such as images of astronomical objects, spectra, data tables, time series, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g., ASCII, html, FITS, HD5, Virtual Observatory-compliant tables, XML files, etc.). Include a description of any metadata that will make the actual data products useful to the general researcher. Where data are stored in unusual or not generally accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies should be provided. "Access to data" refers to data made accessible to an interested party without the need for an explicit request from the interested party. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and contributions of your data to public databases. If maintenance of a web site or data base is the direct responsibility of your group, provide information about the period you plan to maintain the web site or data base. Note that data taken at national or private observatories may already be accessible through a public archive (perhaps after a standard proprietary period). Various forms of data (e.g. FITS images and tables, HD5 or other data tables) also may be deposited with published articles in the AAS journals and other journals. Attention should be paid to making accessible data sets that are products of well-defined surveys. Also describe your practice or policies regarding the release of data, for example whether data are posted before or after formal publication."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing, including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. It is preferred that all data products be made available without requiring a special request to investigators. Describe your policies regarding the use of data provided via general access or sharing. For example, if you plan to provide data and images on your website, will the website contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products (e.g., images) are copyrighted (by a journal, for example), how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. If the data will be archived by a third party (e.g., national observatory or journal), please refer to their preservation plans if available. Special attention should be taken to selecting institutional sites that are expected to have a reasonably long lifetime. The Data Management Plan should describe the types of data, metadata, scripts used to generate the data or metadata, experimental results, samples, physical collections, software, curriculum materials, or other materials to be produced in the course of the project. The Data Management Plan should address the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies). It should also cover any other types of information that would be maintained and shared regarding data, e.g. the means by which it was generated, detailed analytical and procedural information required to reproduce experimental results, and other metadata. The Data Management Plan should address the policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements. It should cover any factors that limit the ability to manage and share data, e.g. legal and ethical restrictions on access to human subject data. The Data Management Plan should address the policies and provision for re-use, re-distribution, and the production of derivatives. The Data Management Plan should address the plans for archiving data, samples, and other research products, and for the preservation of access to them. It should cover the period of time the data will be retained and shared; how data are to be managed, maintained, and disseminated; and mechanisms and formats for storing data and making them accessible to others, which may include third party facilities and repositories. The Data Management Plan should clearly articulate how the PI and co-PIs plan to manage and disseminate data generated by the project. The plan should outline the rights and obligations of all parties as to their roles and responsibilities in the management and retention of research data, and consider changes that would occur should a PI or co-PI leave the institution or project. It should describe how the research team plans to deposit data into any relevant and appropriate disciplinary repositories that are appropriately managed and that are likely to maintain the metadata necessary for future use and discovery. Any costs associated with implementing the DMP should be explained in the Budget Justification. Describe your policies regarding the use of data provided via general access or sharing, or specific licensing provisions, if applicable. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data. Describe the types of data (including metadata and annotations, primary or analyzed) and products that will be generated by the research, for example description of samples, numerical data on chemical systems such as spectra, chemical and physical properties, time-dependent information on chemical and physical processes, theoretical formalisms, experimental protocols, algorith specifications, database schemas and data tables, data produced by simulations and software. Data and products generated from Broader Impact activities, such as educational materials, participant information, tutorials and other web-based materials, as well as assessment results, should also be included in the DMP. Describe the format and media in which the data or products are stored (e.g., hardcopy notebook and/or instrument outputs, ASCII, html, jpeg or other formats). Where data are stored in unusual or not generally-accessible formats, explain how the data may be converted to a more accessible format or otherwise made available to interested parties. In general, solutions and remedies to providing data in an accessible format should be provided with minimal added cost. "Access to data" refers to data made accessible without explicit request from the interested party, for example those posted on a website or made available to a public database. Describe your plans, if any, for providing such general access to data, including websites maintained by your research group, and direct contributions to public databases or software repositories (e.g., NMRShiftDB, the Protein Data Bank, Cambridge Crystallographic Data Centre, Inorganic Crystal Structure Database in Karlsruhe, Zeolite Structure Database and Github). For software or code developed as part of the project, include a description of how users can access the code (e.g. licensing, open source) and specific details of the hosting, distribution and dissemination plans. Also describe your practice or policies regarding the release of data for access, for example whether data are posted before or after formal publication. Note as well any anticipated inclusion of your data in databases that mine the published literature (e.g. PubChem, NIST Chemistry WebBook). Consider using the Digital Object Identifiers (DOI) assignment mechanism not just for journal articles, but for suitably-archived, publishable data sets."Data sharing" refers to the release of data in response to a specific request from an interested party. Describe your policies for data sharing including, where applicable, provisions for protection of privacy, confidentiality, intellectual property, national security, or other rights or requirements. Discussion on the compliance with the NSFs Public Access Policy is also encouraged. Describe your policies regarding the use of data provided via general access or sharing. Practices for appropriate protection of privacy, confidentiality, security, intellectual property, and other rights should be communicated. The rights and obligations of those who access, use, and share your data with others should be defined. For example, if you plan to provide data and images on your website, will the website contain disclaimers or conditions regarding the use of the data in other publications or products? Describe when the data should be archived, how data will be archived, and how preservation of access will be handled. Are there provisions for data backup? Will hardcopy notebooks, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? What are the physical and cyber resources and facilities that will be used for data preservation and storage? Will there be an easily accessible index that douments where all archived data are stored and how they can be accessed? What are the roles and responsibilities of all parties with respect to the management and archiving of the data after the grant ends? How long will the data be maintained after the grant ends?CHE-supported large research centers or other programs may specify more stringent data storage, sharing and archiving procedures for research conducted under their awards. Such requirements will be specified in the program solicitation and award conditions. Describe the types of data and products that will be generated in the research, such as physical samples, space and/or time-dependent information on chemical and physical processes, images, spectra, final or intermediate numerical results, theoretical formalisms, computational strategies, software, and curriculum materials. Describe the format in which the data or products are stored (e.g. hardcopy logs and/or instrument outputs, ASCII, XML files, HDF5, CDF, existence of metadata, etc). Describe your plans for providing access to data, including websites maintained by your research group and contributions to public databases, and the mechanism for making the existence of an archive publicly known (e.g. by indicating the data sharing mechanism in publications that recognize NSF support). If maintenance of a web site or database is the direct responsibility of your group, provide information about the period of time the web site or database is expected to be maintained. Also describe your practice or policies regarding the release of data – for example whether data are available before or after formal publication and the approximate duration of time that the data will be kept private. Describe your policies (where applicable) for protection of propriety data, privacy and confidentiality, intellectual property, or other rights or requirements. Describe your policies regarding the use of data provided via general access or sharing. If you plan to provide data on a website, will the site contain disclaimers, or conditions regarding the use of the data in other publications or products? If the data or products are copyrighted, how will this be noted on the website? Describe whether and how data will be archived and how preservation of access will be handled. For example, will hardcopy logs, instrument outputs, and physical samples be stored in a location where there are safeguards against fire or water damage? Is there a plan to transfer digitized information to new storage media or devices as technological standards or practices change? Will there be an easily accessible index that documents where all archived data are stored and how they can be accessed? If the data will be archived by a third party, please refer to their preservation plans (if available).
Consider which data (or research products) will be deposited for long-term access and where. (What physical and/or cyber resources and facilities (including third party resources) will be used to store and preserve the data after the grant ends?)
Describe your long-term strategy for storing, archiving and preserving the data you will generate or use. Consider the following:What is the long-term strategy for maintaining, curating and archiving the data?Which archive/repository/database have you identified as a place to deposit data?What procedures does your intended long-term data storage facility have in place for preservation and backup?How long will/should data be kept beyond the life of the project?What data will be preserved for the long-term?On what basis will data be selected for long-term preservation?What metadata/documentation will be submitted alongside the data or created on deposit/transf
NSF BIO Guidance
NSF Public Access: Frequently Asked Questions
ESA Data Sharing Resources
DataONE Best Practices
USGS Data Management Best Practices
Guidance
re3data: Registry of data repositories ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
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NSF Frequently Asked Questions (FAQs) for Public Access
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF GEO Data Policies
R2R Scientific Sampling Event Log
BCO-DMO DMP Suggestions for Proposals Involving a Research Cruise (PDF)
IMBER Data Management Cookbook
ROSCOP (Report of Observations/Samples collected by Oceanographic Programmes) Cruise Summary Form
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
Usually, data served by BCO-DMO are submitted as comma- or tab-separated ASCII files (.csv, .txt) or as spreadsheet files (.xls, .xlsx). However, BCO-DMO is flexible and willing to work with whatever reasonably organized format the investigator uses.
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
BCO-DMO Guidance on Organizing Data in a Spreadsheet
DMPTool Guidance on File Formats
Field observation data will be stored in flat ASCII files, which can be read easily by different software packages. Field data will include date, time, latitude, longitude, cast number, and depth, as appropriate. Quality flags will be assigned according to the ODS IODE Quality Flag scheme (IOC Manuals and Guides, 54, volume 3; http://www.iode.org/mg54_3 ). Metadata will be prepared in accordance with BCO-DMO conventions (i.e. using the BCO-DMO metadata forms) and will include detailed descriptions of collection and analysis procedures.
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
DMPTool Guidance on Security and Storage
The investigators will store project data (including spreadsheets, ASCII files, images, and PDFs of scanned logs) on laboratory computers that are backed up by the University’s central IT organization. The Principal Investigator (PI) has also established an account with the San Diego Super Computer’s enterprise class Cloud Service for data storage and sharing among project investigators. Personal computers in all laboratories are backed up daily using Apple Time Machine to an onsite external hard drive, and weekly to an offsite hard drive.Data Sharing via BCO-DMO
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
Data Repositories List (created by Integrated Earth Data Applications (IEDA))
Terms of Use for Data at BCO-DMO
R2R Cruise Catalog
DMPTool Guidance on Copyright and Privacy
Creative Commons License Types
University-National Oceanographic Laboratory System (UNOLS)
National Center for Biotechnology Information (NCBI)
GenBank
Long Term Ecological Research (LTER) Network Data Portal
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies', '
R2R will ensure that the original underway measurements are archived permanently at NODC and/or NGDC as appropriate. BCO-DMO will also ensure that project data are submitted to the appropriate national data archive. The PI will work with R2R and BCO-DMO to ensure data are archived appropriately and that proper and complete documentation are archived along with the data.
NSF Division of Ocean Sciences Sample and Data Policy (PDF)
NSF Data Management and Sharing FAQs
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMO
NSF OCE Sample and Data Policy, May 2011 (PDF)
NSF GEO Data Policies
Each PI will be responsible for sharing his/her subset of data among the project participants in a timely fashion. J. Doe will be responsible for collecting and analyzing the zooplankton sampling data. P. Smith will oversee the molecular biology work and will submit the resulting sequences to the National Center for Biotechnology Information’s (NCBI) GenBank database. The Lead PI, R. Jones, will coordinate the overall data management and sharing process and will submit the project data, including GenBank accession numbers, and metadata to the Biological and Chemical Oceanography Data Management Office (BCO-DMO) who will be responsible for forwarding these data and metadata to the appropriate national archive.
NSF Frequently Asked Questions (FAQs) for Public Access
BCO-DMO Data Management Best Practices Guide (PDF)
How to Get Started Contributing Data to BCO-DMO
Frequently Asked Questions (FAQs) about BCO-DMONSF Dissemination and Sharing of Research ResultsNSF Grant Proposal Guide on DMPsNSF GEO Directorate Guidance', '
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access.
January 2, 2018 https://www.nsf.gov/bfa/dias/policy/dmpdocs/phy.pdfNSF Mathematical & Physical Sciences, Division of Physics (PHY). https://www.nsf.gov/div/index.jsp?div=PHYProposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF Dissemination and Sharing of Research Results. https://www.nsf.gov/bfa/dias/policy/dmp.jspNSF Frequently Asked Questions (FAQs) for Public Access. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18041
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm ', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
Division of Astronomical Sciences (AST)
Advice to PIs on Data Management Plans, 2011 NSF AST division guidance (PDF)Proposal & Award Policies & Procedures Guide (PAPPG), January 2018. https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18001Plans for data management and sharing of the products of research. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_2.jsp#IIC2jNSF 18-1 January 29, 2018, Part II: Award Administration and Monitoring of Grants and Cooperative Agreements-Chapter VI: NSF Awards. https://www.nsf.gov/pubs/policydocs/pappg18_1/pappg_6.jsp#XID4NSF frequently asked questions (FAQs) for Public Access.https://www.nsf.Mid-Scale Innovations Program in Astronomical Sciences (MSIP) Program Solicitation NSF 17-592. https://www.nsf.gov/pubs/2017/nsf17592/nsf17592.htm
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', '
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
Metadata will be collected from <study area> in <enter data formats here (e.g. handwritten lab notebooks, Microsoft Excel files, R scripts)>. All metadata will be transformed into EML files using the Arctic Data Center submission proceedure.
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
Metadata will be collected from <study area> in <enter data formats here (e.g. handwritten lab notebooks, Microsoft Excel files, R scripts)>. All metadata will be transformed into EML files using the Arctic Data Center submission proceedure.
2. What will be the roles and responsibilities of each party and or individual with respect to management of the data
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
Our <research team lead, project manager, data curator, other> will implement and be responsible for maintaining data storage and backup systems, as well as interfacing with data repository personnel. The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for our project.
Code files will be stored within a Github repository. Team members will upload and share code through this repository.
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products, be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center (ADC) please refer to the guidance in the panel on the right.
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Each file will be no larger than __________ . (Examples are 1 MB, 1 GB, 1TB)
The total storage size will be approximately __________ . (Examples are 1 MB, 1 GB, 1TB)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
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Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
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2. What will be the roles and responsibilities of each party and or individual with respect to management of the data
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
__________ will be responsible for __________. (Examples are collecting data, maintaining data storage and backup systems, interfacing with data repository personnel, etc. Make sure to specify the responsibilities for each organization/individual detailed above.)
The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
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__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
Team member will access files through __________. (Examples are the local network, the designated Git repository, etc.)
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products, be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
The data and associated files will be released through the NSF Arctic Data Center. Data and data products will be made available with as few restrictions as possible. These data and metadata will be made freely available for access and use by all via web-based distribution through the NSF Arctic Data Center.
The NSF Arctic Data Center will provide a recommended formal citation, including a persistent identifier or digital object identifier (DOI) for the submitted data which will allow the team members to cite and share the data.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Other groups that may be interested in __________ data are __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify interest expectations for each type of data detailed in your description of data.)
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Each file will be no larger than __________ . (Examples are 1 MB, 1 GB, 1TB)
The total storage size will be approximately __________ . (Examples are 1 MB, 1 GB, 1TB)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
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Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
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2. What will be the roles and responsibilities of each party and or individual with respect to management of the data
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
__________ will be responsible for __________. (Examples are collecting data, maintaining data storage and backup systems, interfacing with data repository personnel, etc. Make sure to specify the responsibilities for each organization/individual detailed above.)
The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
Team member will access files through __________. (Examples are the local network, the designated Git repository, etc.)
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products, be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
The data and associated files will be released through the NSF Arctic Data Center. Data and data products will be made available with as few restrictions as possible. These data and metadata will be made freely available for access and use by all via web-based distribution through the NSF Arctic Data Center.
The NSF Arctic Data Center will provide a recommended formal citation, including a persistent identifier or digital object identifier (DOI) for the submitted data which will allow the team members to cite and share the data.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Other groups that may be interested in __________ data are __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify interest expectations for each type of data detailed in your description of data.)
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What types of data, samples, collections, software, materials, etc. will be produced during your project?
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Each file will be no larger than __________ . (Examples are 1 MB, 1 GB, 1TB)
The total storage size will be approximately __________ . (Examples are 1 MB, 1 GB, 1TB)
What types of data, samples, collections, software, materials, etc. will be produced during your project?
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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2. What will be the roles and responsibilities of each party and or individual with respect to management of the data
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
__________ will be responsible for __________. (Examples are collecting data, maintaining data storage and backup systems, interfacing with data repository personnel, etc. Make sure to specify the responsibilities for each organization/individual detailed above.)
The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
Team member will access files through __________. (Examples are the local network, the designated Git repository, etc.)
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products, be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
The data and associated files will be released through the NSF Arctic Data Center. Data and data products will be made available with as few restrictions as possible. These data and metadata will be made freely available for access and use by all via web-based distribution through the NSF Arctic Data Center.
The NSF Arctic Data Center will provide a recommended formal citation, including a persistent identifier or digital object identifier (DOI) for the submitted data which will allow the team members to cite and share the data.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Other groups that may be interested in __________ data are __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify interest expectations for each type of data detailed in your description of data.)
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What types of data, samples, collections, software, materials, etc. will be produced during your project?
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Each file will be no larger than __________ . (Examples are 1 MB, 1 GB, 1TB)
The total storage size will be approximately __________ . (Examples are 1 MB, 1 GB, 1TB)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What types of data, samples, collections, software, materials, etc. will be produced during your project?
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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2. What will be the roles and responsibilities of each party and or individual with respect to management of the data
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
__________ will be responsible for __________. (Examples are collecting data, maintaining data storage and backup systems, interfacing with data repository personnel, etc. Make sure to specify the responsibilities for each organization/individual detailed above.)
The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3302, 315, 1997, 963, '
__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
Team member will access files through __________. (Examples are the local network, the designated Git repository, etc.)
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products, be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
The data and associated files will be released through the NSF Arctic Data Center. Data and data products will be made available with as few restrictions as possible. These data and metadata will be made freely available for access and use by all via web-based distribution through the NSF Arctic Data Center.
The NSF Arctic Data Center will provide a recommended formal citation, including a persistent identifier or digital object identifier (DOI) for the submitted data which will allow the team members to cite and share the data.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 4, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3306, 315, 1997, 965, '
Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Other groups that may be interested in __________ data are __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify interest expectations for each type of data detailed in your description of data.)
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What types of data, samples, collections, software, materials, etc. will be produced during your project?
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
Each file will be no larger than __________ . (Examples are 1 MB, 1 GB, 1TB)
The total storage size will be approximately __________ . (Examples are 1 MB, 1 GB, 1TB)
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What types of data, samples, collections, software, materials, etc. will be produced during your project?
These data will include the variables __________. (Enter data variables here. Examples are water temperature, water salinity, photosynthetically active radiation, methane flux, soil albedo, etc.)
Additional data products that will be made available include __________. (Enter additional products here. Examples are atmospheric model codes, educational materials, etc.)
What format(s) will data and metadata be collected, processed, and stored in?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 1, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (3315, 316, 2003, 958, '
What format(s) will data and metadata be collected, processed, and stored in?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
All data will be transferred into the following formats for processing and storage: __________ . (Examples are CSV files, NetCDF files, etc.)
Metadata will be collected in __________ . (Examples are handwritten lab notebooks, Microsoft Word files, etc.)
All metadata will be transformed from text into EML files by the Arctic Data Center online submission tool when submitting to the Arctic Data Center.
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1. What parties and individuals will be involved with data management in this project?
2. What will be the roles and responsibilities of each party and or individual with respect to management of the data
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
__________ will be responsible for __________. (Examples are collecting data, maintaining data storage and backup systems, interfacing with data repository personnel, etc. Make sure to specify the responsibilities for each organization/individual detailed above.)
The NSF Arctic Data Center will provide data archival, preservation, access and metadata authoring services for the project.
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Will any of the data and/or related materials produced need provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements? If so describe them and detail any requested exceptions from the archiving requirements set for Arctic Sciences research.
__________ data are expected to need provisions due to __________. (Examples are ethical restrictions, release of indigenous knowledge, etc. Make sure to specify explanations for all expected provisions detailed above.)
Because of these expected provisions, it is expected that __________ data will need to be exempted from the archiving requirements set for Arctic Sciences research.
Team member will access files through __________. (Examples are the local network, the designated Git repository, etc.)
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products, be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
The data and associated files will be released through the NSF Arctic Data Center. Data and data products will be made available with as few restrictions as possible. These data and metadata will be made freely available for access and use by all via web-based distribution through the NSF Arctic Data Center.
The NSF Arctic Data Center will provide a recommended formal citation, including a persistent identifier or digital object identifier (DOI) for the submitted data which will allow the team members to cite and share the data.', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 3, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
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Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
How do you anticipate the data for this project will be used? Consider the following:
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Other groups that may be interested in __________ data are __________. (Examples are academic researchers, government agencies, non-profit organizations, etc. Make sure to specify interest expectations for each type of data detailed in your description of data.)
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What is the long-term strategy for maintaining, curating, and archiving the data?
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
1. What parties and individuals will be involved with data management in this project?
2. What will be the roles and responsibilities of each party and or individual with respect to management of the data?
3. Who will be the lead or primary person responsible for ultimately ensuring compliance with the Data Management Plan?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What types of data, samples, collections, software, materials, etc. will be produced during your project?
What types of data, samples, collections, software, materials, etc. will be produced during your project?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What format(s) will data and metadata be collected, processed, and stored in?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
What format(s) will data and metadata be collected, processed, and stored in?
Note: if you plan to submit data to the Arctic Data Center please refer to the guidance in the panel on the right.
How will data be accessed and shared during the course of the project?
Note: Arctic Observing Network (AON) data must be deposited in a long-lived and publicly accessible archive within 6 months of collection, and Arctic Social Science Program (ASSP) research data must be deposited in a long-lived and publicly accessible archive within 5 years of the award date assuming no exceptions to the archiving requirements are requested.
How do you anticipate the data for this project will be used? Consider the following:
Which bodies/groups are likely to be interested in the data?What and who are the intended or foreseeable uses/users of the data?
', '', '', '
Note: If you are planning on restricting access, use, or dissemination of the data, you must explain in this section how you will codify and communicate these restrictions.
What is the long-term strategy for maintaining, curating, and archiving the data?
Note: The Office of Polar Programs policy requires that metadata files, full data sets, and derived data products be deposited in a long-lived and publicly accessible archive.
The following questions are intended to assist PIs and panel members to prepare Data Management Plans and to evaluate them during merit review, respectively. The questions are sequential, that is, if (1) applies, then the remaining questions are irrelevant unless (2) also applies or the PI chooses to deposit the data or software in multiple repositories. The more detailed questions, (4)-(6), apply if (1) and (2) do not.Does the solicitation specify a repository for the data or software?Does the PIs home institution have an institutional repository that mandates local deposit of the data/software?Is there a discipline-relevant repository used by the research community either as the expected repository for data/software or as the expected repository for discovering and reusing data/software?Is the repository sustainable? And if not, are there contingency plans?Does the repository require at least minimal identification and description of the data product sufficient to enable discovery, access, and retrieval? For purposes of data citation, NSF requires a persistent identifier and some level of metadata including acknowledgment of the creator/author and federal support.Has the PI made any contingency plans in the event a designated repository becomes unavailable?', '', '', '', '{"meta": {"schemaVersion": "1.0"}, "type": "textArea", "attributes": {"cols": 20, "rows": 2, "asRichText": true}}', 0, 2, @default_funder2_id, CURDATE(), @default_funder2_id, CURDATE());
-INSERT INTO versionedQuestions (id, versionedTemplateId, versionedSectionId, questionId, questionText, requirementText, guidanceText, sampleText, json, useSampleTextAsDefault, displayOrder, createdById, created, modifiedById, modified) VALUES (5337, 478, 3058, 3358, 'Describe the types of data and products to be produced during the project. Examples of data and products include: materials samples; characterization data; (meta)data that provides information on the data, e.g. synthesis conditions or community codes used; simulation data; and software. Data and other products generated from Broader Impact activities, such as education materials and assessment results, should also be included in the plan, together with Institutional Review Board (IRB) considerations and clearance, if applicable. This inventory should inform the scope of the Data Management Plan and the requirements to preserve, curate, and share the products that result from the project.', '', '