DCB Guidance for the NIH Data Management and Sharing (DMS) Policy

Aims of the NIH DMS Policy:

• To promote a culture in which Data Management and Sharing are an integral component of a biomedical research project, rather than an administrative or additive one.
• Data Management and sharing practices are consistent with the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles.
• All research grants that generate scientific data include a DMS Plan where investigators have prospectively planned on how to preserve and share scientific data with the scientific community.

Additional information about Sharing Data can be found at an NCI Office of Data Sharing webpage.

Every NIH grant applicant with application receipt due dates for or after January 2023, must provide a Data Management and Sharing (DMS) Plan. NIH expects that applicants will maximize appropriate data sharing.

A DMS Plan must reflect the proposed approach to data management and sharing at the time it is prepared and must be updated throughout the life of the project, as appropriate. NIH encourages data management and sharing practices to be consistent with the FAIR data principles and reflect best practices within specific research communities.

The NIH Genomic Data Sharing Policy (GDS) is now harmonized into the DMS Policy, so the single DMS Plan should satisfy requirements of both the GDS policy and the DMS policy if large-scale omics data are being generated.

Updated elements of an NIH DMS Plan were shared in NOT-OD-26-046.

An updated DMS Plan Format page will be made available upon receipt of OMB clearance. A draft can be viewed at the Data Management and Sharing Plan Format Page. 

Data Management and Sharing Plan Elements should include only the following:

1. Will there be maximum appropriate sharing of scientific data underlying peer-reviewed publications and other findings resulting from the work supported by this award (including preprints, referenced papers reported at conferences, and other findings)? 

   [YES/NO]

2. Will the scientific data underlying peer-reviewed publications be shared by the time of publication or, for other findings, by the end of the period of performance, which includes no-cost extensions? 

   [YES/NO]

3. Will shared scientific data be made available for at least as long as required by applicable data repository policies and/or journal policies?

   [YES/NO]

4. If you answered “NO” to elements 1, 2, or 3, or if you anticipate that sharing will be limited in some other way, please describe these limitations and the ethical, legal, or technical factors for them (see an example in NIH DMS FAQ B.5). Your response should specify a particular reason(s) for limiting sharing. 

   [Response = 300 words maximum]

5. If scientific data derived from human research participants will be shared, will privacy, rights, and confidentiality of participants be protected as outlined in Supplemental Information to the NIH Policy for Data Management and Sharing: Protecting Privacy When Sharing Human Research Participant Data (NOT-OD-22-213), including whether any scientific data will be shared using access controls? 

   [YES/NO]

6. In the table below, please list (100 words maximum):

   - Key types of scientific data anticipated to be generated during the project, including the species and modality, if known (e.g., “human genomic data,” “rat functional magnetic resonance imaging data”). NIH recognizes that not all data types expected to be generated in the study will meet the definition of scientific data or can be anticipated in advance. If a data type does not appear on the list, it does not imply that that data type will not be shared if it is generated in the study.

   -The repository or an example of a repository where the scientific data may be managed and shared, if the scientific data is known at time of application. NIH expects the use of established repositories for preserving and sharing scientific data when they are available.

   Expected Data Type	Expected Repository or Example

7. For studies subject to the NIH Genomic Data Sharing Policy (GDS) (e.g., using NIH funds to generate large-scale human genomic data):

   - Will you share all large-scale human genomic and associated data in a NIH-designated repository according to the accelerated timelines expected in the GDS Policy?

   [YES/NO/Not Applicable]; If “NO,” address in element 4.

   - Do you anticipate that when sharing large-scale human genomic data that you will be able to meet the expectations of the Institutional Certification in the GDS Policy? 

   [YES/NO/Not Applicable]; If “NO,” address in element 4.

• Information related to the 6 elements required in an NIH DMS Plan for applications with a receipt date before May 25, 2026.

Details about reporting DMS activities in section C5.c of Research Performance Progress Reports (RPPRs) and processes for requesting revisions to an approved DMS Plan can be found in a document with DMS Policy Updates (as of Jan. 2025). 

Additional information can also be found in the NIH Guide for Grants and Contracts:

• NOT-OD-24-175: Reporting Data Management and Sharing (DMS) Plan Activities in Research Performance Progress Reports (RPPRs) Submitted on or After October 1, 2024
• NOT-OD-24-176: Updated Processes for Requesting Revisions to an Approved Data Management and Sharing (DMS) Plan

Metadata

Data that are preserved and shared should be accompanied by their metadata and other associated relevant documentation. Metadata are data about how a dataset or resource came about and how it is internally structured (e.g. the unit of analysis, collection method, sampling procedure, sample size, categories, variables, etc.).

If no metadata standards are defined for the data types/research field, provide minimum information that someone would need to know to be able to work with the dataset without any further input from you. It is recommended to think as a consumer of the data, not the producer. 

Data Standards

Data standards are pivotal for enabling interoperability of datasets and resources. A data standard is defined as a type of standard, which is an agreed upon approach to allow for consistent measurement, qualification or exchange of an object, process, or unit of information. 

Widely accepted research standards should be used, and it is recommended to use the data standard requirements of established repositories where the data is planned to be submitted.

Examples of some community data standards for various data types:

List the repository or repositories where scientific data and metadata generated will be archived. It is encouraged to preserve and share data through established repositories.

Here are lists of repositories where scientific data generated from an NIH-funded award can be deposited and archived:

1. NIH Supported Repositories
2. Generalist Repositories 

NIH encourages the use of domain-specific repositories where possible; however, such repositories are not available for all datasets. When researchers cannot locate a repository for their discipline or the type of data they generate, a generalist repository (which accepts data regardless of data type, format, content, or disciplinary focus) can be a useful place to share data.

Desirable attributes of repositories where scientific data generated from an NIH-funded award can be deposited include:

• Unique persistent identifiers
• Long-term sustainability
• Metadata
• Curation and quality assurance
• Free and easy access
• Broad and measured reuse
• Security and integrity
• Confidentiality
• Provenance
• Retention policy

• NIH Data Management and Sharing (DMS) Policy Website
• NCI Office of Data Sharing webpage on
  How to Write a Data Management and Sharing (DMS) Plan
• NCI Office of Data Sharing webpage on Data Sharing and Policy Guidance
• NIH Science and Technology Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) initiative Website 

If you have DCB-related questions about the NIH DMS Policy, please contact Dr. Soumya Korrapati.