NIH Data Management and Sharing Policy


The National Institutes of Health (NIH) issued the Data Management and Sharing (DMS) Policy (effective January 25, 2023) to promote the sharing of scientific data. Sharing scientific data aids in accelerating biomedical research discovery by enabling validation of research results, providing accessibility to high-value datasets, and promoting data reuse for future research endeavors.

NIH's policy applies to all research meeting these criteria regardless of funding level:

  • Funded or conducted in whole or in part by NIH
  • Results in the generation of scientific data

Scientific Data is defined as data commonly accepted in the scientific community of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications.

  • Scientific data includes any data needed to validate and replicate research findings
  • 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


The DMS Policy does not apply to research and other activities that do not generate scientific data.
Examples include: Training (Ts), Fellowships (Fs), Certain non-research Career Awards (e.g. KM1), Construction (C06), Conference Grants (R13), Resources (Gs), Research-related Infrastructure programs (e.g., S06) and non-research activities.

Data Management and Sharing Plan Checklist for Researchers

This Data management and Sharing (DMS) Plan Checklist addresses the six required elements from the NIH DMS Policy, effective Jan. 25, 2023 for all new grant proposals. Review the checklist at

Converting a resource sharing plan into a DMS Plan

The following is a sample plan created by a working group from the NIH DMSP Guidance:

CITI DMS Information webinar

CITI is offering a DMS information webinar to provide more information on converting a resource sharing plan into a DMS plan, FAQs, links to important DMS information and more. To review, sign in or create a CITI account (free using your access ID) at this link (click here.) If you have a problem creating an account, please contact Ginette Borovicka via email.

Frequently Asked Questions

The National Institutes of Health has developed a page with frequently asked questions based on the following:

  • Policy scope
  • Managing/sharing scientific data
  • Considerations for scientific sata derived from human participants
  • Compliance and enforcement
  • Contracts
  • Budget/costs

To view these FAQs, visit

  • Part 1: NIH DMS Plan Overview


    • Submit DMS plan with proposal
    • NIH program staff assess plans
    • Plans returned for modification if insufficient or unacceptable
    • Becomes part of award terms and conditions and will be monitored

    [Reapproval of DMSP mandatory if new scientific direction, change in repository or timeline]

    What proposal activities require DMS?

    All research generating scientific data, including but not limited to:

    • Research Projects
    • Contract Proposals
    • Certain Career Development Awards (Ks)
    • Small Business SBIR/STTR
    • Research Centers
    • Other Funding agreements with the NIH [e.g., Other Transactions]

    What proposal activities are exempt from DMS?

    Research projects not generating scientific data or non-research projects, including but not limited to:

    • Training (Ts)
    • Fellowships (Fs)
    • Certain non-research Career Awards (e.g., KM1)
    • Construction (C06)
    • Conference Grants (R13)
    • Resources (Gs)
    • Research-Related Infrastructure Programs (e.g., S06)

    What counts as data for sharing?

    • Adequate data to validate and replicate study findings
    • Data resulting from the study but not necessarily supporting a publication
    • Null findings that do not result in a publication

    What scientific data are exempt from DMS?

    • Data not necessary for or of sufficient quality to validate and replicate research findings,
    • Laboratory notebooks
    • Preliminary analyses
    • Completed case report forms
    • Drafts of scientific papers
    • Plans for future research
    • Peer reviews
    • Communications with colleagues, or  
    • Physical objects, (e.g., laboratory specimens) 

    What limitations are there on data sharing?

    Justifiable ethical, legal and technical factors for limiting sharing include:

    • Informed consent will not permit or limits scope of sharing or use
    • Privacy or safety of research participants would be compromised and available protections insufficient
    • Explicit federal, state, local, or Tribal law, regulation, or policy prohibits disclosure
    • Restrictions imposed by existing or anticipated agreements with other parties

    What does not justify limiting data sharing?

    • Data are considered too small
    • Researchers anticipate data will not be widely used
    • Data are not thought to have a suitable repository 

    When must data be shared?

    • Data must be shared no later than publication of findings or end of award

    What policies apply to my research? Tool for determining:


  • Part 2: Content of a NIH Data Management & Sharing Plan

    What must be included in a DMS plan? 

    • Data Type 

    • Description, dictionary, study protocol,

    • Collection instruments 

    • Modality: imaging, genomic, survey 

    • Level of aggregation: individual, grouped, summarized 

    • Level of data processing: raw v. processed data 

    • Genomic Data Sharing 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 

    • Related Tools, Software and/or Code 

    • Any additional tools/software needed to access or manipulate data 

    • Names of specific software tools 

    • Availability of tools 

    • Expected lifespan of the tools v. length of data availability 

    • Standards [ e.g., OnCore, REDCap ...] 

    • Data formats 

    • Data dictionaries 

    • Common data elements 

    • Identifiers 

    • Definitions 

    • Indicate if no consensus standard exists 

    • Data Preservation, Access and Associated Timelines 

    • Name of repository where data and meta data will be deposited 

    • How will data be made identifiable 

    • When the data will be available and for now long 

    • For data subject to the Genomic Data Sharing Policy: 

    • For human genomic data: 

    • For Non-human genomic data: 

    • Investigators may submit data to any widely used repository. 

    • 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. 

    • Access, Distribution or Reuse Considerations 

    • Limitations due to informed consent, privacy or confidentiality protections 

    • Controlled access protections (e.g., author approval, DUA) 

    • Restrictions imposed by federal, tribal or state laws, regulations or policies (e.g., HIPAA) 

    • Expectations for human genomic data subject to the GDS Policy: 

    • Informed Consent Expectations:  

    • For research involving the generation of large-scale human genomic data from cell lines or clinical specimens that were created or collected AFTER the effective date of the GDS Policy (January 25, 2015): 

    • NIH expects that informed consent for future research use and broad data sharing will have been obtained. This expectation applies to de-identified cell lines or clinical specimens regardless of whether the data meet technical and/or legal definitions of de-identified (i.e. the research does not meet the definition of “human subjects research” under the Common Rule). 

    • For research involving the generation of large-scale human genomic data from cell lines or clinical specimens that were created or collected BEFORE the effective date of the GDS Policy: 

    • There may or may not have been consent for research use and broad data sharing. NIH will accept data derived from de-identified cell lines or clinical specimens lacking consent for research use that were created or collected before the effective date of this Policy.  

    • Institutional Certifications and Data Sharing Limitation Expectations: 

    • DMS Plans should address limitations on sharing by anticipating sharing according to the criteria of the Institutional Certification. 

    • In cases where it is anticipated that Institutional Certification criteria cannot be met (i.e., data cannot be shared as expected by the GDS Policy), investigators should state the institutional Certification criteria in their DMS Plan, explaining why the element cannot be met, and indicating what data, if any, can be shared and how to enable sharing to the maximal extent possible (for example, sharing data in a summary format). In some instances, the funding NIH ICO may need to determine whether to grant an exception to the data submission expectation under the GDS Policy. 

    • Genomic Summary Results:  

    • Investigators conducting research subject to the GDS Policy should indicate in their DMS Plan if a study should be designated as “sensitive” for the purposes of access to Genomic Summary Results (GSR), as described in NOT-OD-19-023. 

    • Oversight of DMS plan 

    • Describe how compliance will be monitored & managed 

    • Identify key roles within research project 

    Formatting a NIH Data Management & Sharing policy 

    • Hypertext (URLs, web links, etc.) prohibited 

    • Recommended length is two pages 

    • Use appropriate template and/or refer to example plans [see Appendix] 

    • Use DMPTool – free, online data management sharing plan tool: 

    [use the single sign on (SSO) using your WSU AccessID] 

    [recording of December webinar; includes PPT slides] 

    • Upload as PDF into 398 Research Plan tab in grant package 

  • Part 3: Repositories and Costs

    What are desired characteristics of a repository? 

    Unique Persistent Identifiers 

    Clear use guidance 

    Long term sustainability 

    Security and integrity 



    Curation and Quality Assurance 

    Common format 

    Free and easy access 


    Broad and measured reuse 

    Retention Policy 

    Repository Options: 

    What costs are involved in a DMS plan and can it be part of the proposal budget? 

    • Allowable Costs: Include as 1a single line item in budget but separate personnel from non-personnel in budget justification. If no costs budgeted for DMS plan, explain in budget justification:

      • Curating data 

      • Developing supporting documentation 

      • Formatting data to accepted standards, or for transmission to and storage at repository for long-term preservation & access

      • De-identifying data 

      • Preparing metadata to foster discoverability, interpretation and reuse 

      • Local data management considerations, e.g., unique or specialized information infrastructure necessary to provide local management and preservation 

      • Preserving and sharing data through established repositories, such as data deposit fees

    If the Data Management & Sharing (DMS) plan proposes deposition to multiple repositories, costs associated with each proposed repository may be included. 

    Note that all allowable costs submitted in budget requests must be incurred during the performance period, even for scientific data and metadata preserved and shared beyond the award period.  

    For instance, if a DMS plan proposes preserving and sharing scientific data for 10 years in an established repository with a deposition fee, the cost for the entire 10-year period must be paid before the end of the period of performance. 

    • Unallowable Costs:

      • Infrastructure Costs that are included in institutional overhead (F&A) 

      • Costs associated with routine conduct of research, including costs associated with collecting or gaining access to research data 

      • Costs that are double-charged or inconsistently charged as both direct and indirect costs 

    • See sample budget estimation tool in Appendix (forthcoming)


  • Part 4: Data Management and Sharing Templates & Other Resources

    Data Managment & Sharing Plans


    NIH Center or Institute

    Sample Plan A   Clinical and/or MRI data from human research participants NIMH
    Sample Plan B   Genomic data from human research participants NIMH
    Sample Plan C   Genomic data from a non-human source NIMH
    Sample Plan D   Secondary data analysis NIMH
    Sample Plan E   Human genomic data NHGRI
    Sample Plan F   Technology development NHGRI
    Sample Plan G   Human clinical and genomics data NICHD
    Sample Plan H   Gene expression analysis data from non-human model organism (zebrafish) NICHD
    Sample Plan I   Human survey data NICHD

    Data Management and Sharing Plans - templates and examples 

    Data Management and Sharing Plan Decision Tree 

    Data Management and Sharing Plan (Word format)

    Planning for Long-term use of Biomed Data (pdf) (book) 

    NDA Data Submission Cost Estimation Tool.xlsx 


    Convenient Webinar Links [contains interval stops]: 

    Webinar I: Understanding the New NIH Data Management and Sharing (DMS) Policy  and Q&A from Webinar I

    Webinar II: Diving Deeper into the new NIH Data Management and Sharing Policy and Q&A from Webinar II 

  • Part 5: Data Management and Sharing Plan Oversight

    During this period when Institutional Policy for DMS plan oversight is under development, project PD/PIs will be responsible for the development of plans that meet NIH requirements as well as data entry, maintenance of data, any annual communication with NIH regarding the DMS plan, and obtaining required reapproval of DMS Plans, i.e., reapproval is mandatory if there is a new scientific direction or a change in the repository or timeline for making data publicly available.