The National Institutes of Health (NIH) implemented a new data management and sharing policy (DMSP) on January 25, 2023. High-level aspects of the policy are below:
- Requires submission of a Data Management & Sharing (DMS) Plan with the grant application, and compliance with that Plan as it was approved by NIH program staff (plans are reviewed, not scored).
- Applies to new applications and renewals submitted on or after January 25, 2023 (does not apply to any applications prior to that date).
- Applies to all research funded whole or in part by NIH that generates scientific data, including clinical data.
- Specific offices and institutes (e.g., National Institute of Mental Health) may have additional DMS Plan requirements.
- DMS Plans should be 2 pages long.
- DMS Plans can be updated throughout the lifecycle of the grant.
- NIH Data Management & Sharing Policy Overview
- NIH DMSP FAQs
- Quick videos and workshops from UMN Research Data Services
- UMN Research Data Services, a partnership between the Libraries and CLA's LATIS, offers education, training, and consultation on data management and data sharing across all disciplines. See contact information in the left pane.
- For DMS Plan review, please send a google document draft to firstname.lastname@example.org, and we will review it within three business days. We may also request to meet with you to discuss the initial review, and will need two to three days to schedule that.
Find a repository
Steps for finding a data repository
- Check your Notice of Funding Opportunity or with your NIH Institute, Center, or Office (ICO) to determine whether either encourages the deposit of data into a specific data repository.
- Explore the list of NIH-Supported Data Sharing Resources to see whether a repository listed under your ICO, subject area, or model system is a good fit for your data.
- Share in a general data repository or DRUM.
UMN data repository memberships
- Inter-University Consortium for Social and Political Research (ICPSR) is a repository for social science research. It offers full curation, member-only, and restricted access to data. Learn more about depositing in ICPSR.
- Dyrad is a repository for the sciences, but also takes general data. It offers workflows for peer review of data and open-access data sharing.
Data Repository for the University of Minnesota (DRUM)
- DRUM is a free public-access repository with no associated curation or deposit fees.
- DRUM meets many of the NIH and OSTP recommended features of data repositories.
- However, DRUM is not suitable for all kinds of data. See limitations below:
- Human Participant Data Policy: data should be non-sensitive, de-identified, and have clear participant consent for open-access sharing.
- Data Collection Policy: data should be owned by the depositor or depositors must have clear rights to share, and documentation should be sufficient to understand the data.
- DRUM is not a good fit for large datasets (individual files over 3GB and submissions over 50GB total), which are difficult to both submit and access through DRUM.
|Offers controlled/ restricted access||no||yes||yes||yes||no||yes|
|Who controls access requests||n/a||repository||repository||depositor||n/a||depositor|
|Fee for data deposit||no||no for UMN||no||no||no for UMN||no|
|Fee for data access||no||for non-members||no||no||no||no|
|Allows blind peer review||no||no||no||no||yes||yes|
Generalist Repository Comparison Chart maintained by NIH
Data Repository Finder maintained by NNLM
Budget for data sharing
NEW: Starting October 5th, 2023, NIH allows DMS costs to be budgeted in whatever budget category is appropriate to the actual cost (e.g., salaries, fringe benefits, other direct costs, etc.) This will expedite award setup. See NIH Application Instruction Updates - Data Management and Sharing (DMS) Costs for details.
NIH DMSP Budgeting Resource prepared by UMN Research Data Services and Sponsored Projects Administration.
Forecasting Costs for Preserving, Archiving, and Promoting Access to Biomedical Data from National Academies of Science, Engineering, and Medicine.
COGR Review of the Final NIH Policy for Data Management and Sharing: Budgeting and Costing from Council on Governmental Relations' NIH Data Management and Sharing Readiness Guide.
Human participant considerations
When collecting data from and with human participants and communities, Element 5.C. of the DMS Plan requires that you describe protection of participants including de-identification of the data. Be explicit in the process you will use to address direct and indirect identifiers.
- Direct identifiers should be completely removed from data. This includes the 18 identifiers described in the HIPAA Safe Harbor Method and any other information that directly ties to an individual.
- Indirect identifiers require close examination for variables - that when combined with other variables, datasets, or publicly available information - could re-identify participants.
- The process of data curation usually involves some level of inspection for direct and indirect identifiers. Not all data repositories have data curators, and if they do, curation may not be a free service.
- Note that a de-identified dataset is not anonymized. When crafting DMS Plans, IRB applications, and participant agreements, using language such as "de-identified" or "confidential" is preferred.
- Guidance regarding methods for de-identification of protected health information in accordance with the HIPAA Privacy Rule
- Johns Hopkins' 5 steps for removing identifiers from datasets
- Consortium of European Social Science Data Archives’ anonymization of quantitative & qualitative data
- Finnish Social Science Data Archive anonymisation template
- Human participant data essentials primer by the Data Curation Network
- Qualitative data primer by the Data Curation Network
Informed consent language
When collecting data from and with human participants and communities, Element 5.A. of the DMS Plan requires that you describe how informed consent will be obtained for data sharing, and if there will be any access restrictions to the data related to consent. Be explicit in the language you will use in the consent form given that the Certificate of Confidentiality (issued to all NIH awardees) requires explicit consent for data sharing. Include:
- How the data will be processed before it is shared, including de-identification methods
- What data will be shared (and what data will not be shared)
- Where the data will be shared (name the specific repository)
- How the data will be accessed (publicly available or restricted to specific requesters)
- Who will grant access (the repository or the PI)
Templates and examples
NIH DMS Plan template in DMPTool
- Log in to DMPTool using your UMN credentials to see DRUM-specific language and submit your DMS Plan to Research Data Services for review.
NIH institutes, centers, and offices may provide more specific guidance
- Look at the website of your specific funder to check for additional requirements. Below are a few examples.
Data Management Plan Database (browse and/or submit your own plan) by McMaster University
UMN examples (forthcoming)
DRUM boilerplate language
- Review DRUM policies to ensure your data can be shared in the institutional repository.
- This language may be copy/pasted into Element 4.A. of the DMS Plan and/or you can split the text below into Elements 4.A., 4.B., 4.C., and 5.B.
"The data will be shared via the Data Repository for the University of Minnesota (DRUM), an open access, publicly-accessible, institutional repository. DRUM has been certified since 2017 by CoreTrustSeal, an international community-based organization that recognizes sustainable and trustworthy repositories. Curators review submissions and work with data authors to comply with data sharing requirements in ways that make data findable, accessible, interoperable, and reusable (FAIR) - including, but not limited to, file transformation and metadata augmentation (Dublin Core is the metadata standard). DRUM commits to 10 years of long-term preservation using services such as file migration (limited format types), off-site backup, bit-level checksums, and Digital Object Identifiers (DOI) for archival citations. The DOI exposes data to online discovery tools like Google Scholar and Web of Science Data Citation Index."
- DRUM will accept data that meet its human participant data and collection policies. To request a specific letter of support for your grant, please send a request and any required template language to email@example.com.
Open Science Framework boilerplate language
Note: Be sure to use the template without hyperlinks for your DMS Plan, as links are not allowed.
General DMP Checklist
- Note: this is a general data management plan checklist useful for NSF, DOE, and other national agencies. It is not specific to NIH's DMS Plan requirements.