NIH Data Management and Sharing Policy (2023)
This page is intended to inform the UMMC community about the new NIH policy, linking to appropriate information and resources whenever possible. It will be updated as new information becomes available, so please check back frequently.
Data Management Plans Overview
A data management plan documents the lifecycle of your data. The plan provides details on data collection for storage, access, sharing, and reproducibility of your results. A good data management plan will ensure the availability and accessibility of your research results after your project is complete and you have published the results, increasing the value of your research and possible reuse by other researchers.
What's new about the 2023 NIH Data Management and Sharing Policy?
Previously, the NIH only required grants with $500,000 per year or more in direct costs to provide a brief explanation of how and when data resulting from the grant would be shared.
The 2023 policy is entirely new. Beginning in 2023, ALL grant applications or renewals that generate Scientific Data must now include a robust and detailed plan for how you will manage and share data during the entire funded period. This includes information on data storage, access policies/procedures, preservation, metadata standards, distribution approaches, and more. You must provide this information in a data management and sharing plan (DMSP). The DMSP is similar to what other funders call a data management plan (DMP).
The DMSP will be assessed by NIH Program Staff (though peer reviewers will be able to comment on the proposed data management budget). The Institute, Center, or Office (ICO)-approved plan becomes a Term and Condition of the Notice of Award.
What do I need to do?
A DMSP must be submitted as part of the funding application for all new and competing proposals/renewals that generate Scientific Data for January 25, 2023, and subsequent receipt dates. The term Scientific Data is defined in the policy 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. Scientific data do 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."
High-level first steps
- Determine your personal timeline. If you have an active NIH award going up for renewal with receipt date of January 2023, or if you are planning to submit an NIH proposal this year, then developing a DMSP should be a high priority, especially if you are working with external collaborators as it may take time to set up appropriate data procedures/agreements.
- Read through this webpage to familiarize yourself with the changes and with the policy itself (including the supplements)
- Familiarize yourself with the FAIR principles (Wilkinson et. al, 2016). The FAIR (findable, accessible, interoperable, reusable) data principles are the guiding principles the NIH has used in creating the new policy.
- Assess your own project and data management practices relative to the policy (see the NIH-provided supplements below), especially around documenting existing practices and developing new ones to address the increased emphasis on data sharing and administrative oversight.
- Review campus data services (e.g., computing, storage, consulting) and assess whether they will meet your needs. Also consider costs you may need to budget for such as labor for data cleaning and documentation (see the NIH-provided supplement on allowable costs).
If your research requires IRB approval, UMMC's Human Research Office (HRO) may ask for information contained in your DMSP. Therefore, it is strongly recommended to draft your DMSP prior to seeking IRB approval.
Data Management Plan Considerations
Although DMP requirements vary by funding agency, your plan will typically need to address the following topics:
- What type of data is it - numeric, text, images? What format is it in?
- How much data will there be?
- How will the data be collected or generated, and for how long? What tools and methodologies will be used?
- Will you be using secondary data? What is the source of the data?
- Who is responsible for managing the data and implementing the data management plan?
Data and Metadata Standards:
- What data and metadata standards will be used? If there are no existing standards, how will this be addressed?
- What file formats and naming conventions will be used? How will the data be organized?
- How will the metadata be managed and stored?
Data Access, Sharing, and Re-Use:
- Does the project involve human subject data? If so, what are your plans to protect and anonymize the data?
- Are there any intellectual property considerations that need to be addressed?
- Are there any patent or licensing restrictions to be considered?
- How should the data be attributed?
Archiving and Preservation:
- Where will the data be archived, and for how long?
- Is there a discipline-specific repository available?
- What software or tools should be archived with the data to facilitate re-use?
For a more comprehensive list of items that could be included in a data management plan, visit:
To learn more about the NIH Policy for Data Management and Sharing, please visit the links below. You can also watch NIH webinars about the new policy
Writing a DMS Plan
A DMS Plan should include the following elements:
- Data Type
- Related Tools, Software and/or Code
- Data Preservation, Access, and Associated Timelines
- Access, Distribution, or Reuse Considerations
- Oversight of Data Management and Sharing
NIH has provided sample DMS Plans as examples of how a DMS Plan could be completed in different contexts, conforming to the elements described above. These sample DMS Plans are provided for educational purposes to assist applicants with developing Plans but are not intended to be used as templates and their use does not guarantee approval by NIH.
Note that the sample DMS Plans provided below may reflect additional expectations established by NIH or specific NIH Institutes, Centers, or Offices that go beyond the DMS Policy. Applicants will need to ensure that their Plan reflects any additional, applicable expectations (including from NIH policies and any ICO- or program-specific expectations as stated in the FOA).
Budgeting for DMS Activities
- The new DMS Policy allows researchers to budget for data management and sharing activities. Reasonable costs may be included in NIH budget requests for:
- Curating data
- Developing supporting documentation
- Formatting data according to accepted community standards, or for transmission to and storage at a selected repository for long-term preservation and access
- De-identifying data
- Preparing metadata to foster discoverability, interpretation, and reuse
- Local data management considerations, such as unique and specialized information infrastructure necessary to provide local management and preservation (for example, before deposit into an established repository)
- Preserving and sharing data through established repositories, such as data deposit fees
Costs must be incurred during the performance period.