The best time to formulate a data management and sharing plan is before you start to collect research data. Having a management plan in place before the study begins ensures the data will be organized, well documented, and stored securely during the project and long after it is completed. Waiting until the end of a project often results in lost data, lack of notes, or sometimes a lack of proper permissions to even analyze and publish a particular dataset. In addition, funding agencies increasingly require data management and sharing plans to be included with grant applications to promote open science and improve rigor and reproducibility. Developing a data management plan from the start requires effort, but it will save you valuable time and effort down the road.
On this page:
NIH Data Management and Sharing Plans
- Applications for Receipt Dates BEFORE Jan 25, 2023
- Applications for Receipt Dates ON/AFTER Jan 25, 2023
Under the new 2023 NIH Data Management and Sharing (DMS) Policy, all applicants planning to generate scientific data must prepare a DMS Plan describing how the scientific data will be managed and shared. In preparation for the new NIH DMS policy, the NIH released a new scientific data sharing website in April 2022, providing guidance on how to write a data management and sharing plan. In August 2022, the NIH released an Implementation Details Notice (NOT-OD-22-189) providing an optional DMS Plan format page which will be converted to a final fillable format page by Fall 2022.
Applications subject to NIH’s Genomic Data Sharing (GDS) Policy should also address GDS-specific considerations within the elements of a DMS Plan.
- Elements to Include in a Data Management and Sharing Plan
- Assessment of Data Management and Sharing Plans
- Revising Data Management and Sharing Plans
Note that funding opportunities or ICs may have specific expectations (for example: scientific data to share, relevant standards, repository selection). View a list of NIH Institute and Center data sharing policies. Investigators are encouraged to contact program officers with questions about specific ICO requirements.
NIH Genomic Data Sharing Plans
- Applications for Receipt Dates BEFORE Jan. 25 2023
- Applications for Receipt Dates AFTER Jan. 25 2023
To reduce the burden on applicants and staff, NIH harmonized sharing plans with a single data sharing plan at time of funding application satisfying both the Genomic Data Sharing (GDS) Policy and the DMS Policy (NOT-OD-22-198). Therefore, on or after Jan. 25, 2023, separate GDS Plans WILL NOT be accepted.
Genomic data sharing considerations, such as where and when genomic data will be shared, will be expected to be addressed in DMS Plans using the DMS Plan elements.
DMPTool
While different funders have different requirements around what a plan should look like, the DMPTool, a free web-based tool created and maintained by the California Digital Library (CDL), can help investigators compose a plan that meets the requirements of their specific funder. Sign in through Washington University’s DMPTool affiliation using your WUSTL Key and follow these instructions on how to use the DMPTool to get started.
The DMPTool provides general boilerplate text and guidance based on specific funding-agency requirements in a simple-to-use online template. As of August 2022 the DMPTool has 43 funder-specific templates. That number will continue to grow as more funding agency templates and NIH IC-specific policy components are added to the general NIH-DMSP template. Funder-specific requirements compiled by the DMPTool can be found here and you can also visit our Data Management and Sharing Policies page to learn more. While templates in the DMPTool are based on the requirements listed in the funder’s policy documents, researchers should consult the program officers and policy documents directly for authoritative guidance.
In March 2022, the DMPTool added “featured” public plans to highlight example data management and sharing plans that people can use as a reference when writing their own plan. Instructions for how to use example plans can be found here: “How to Find Example plans in the DMPTool.”
Another advantage of using the DMPTool is that it allows you to request feedback from your institutional DMPTool admins directly within the DMPTool before finalizing your plan. Washington University institutional DMPTool admins are located in Becker Library at the School of Medicine and University Libraries on the Danforth Campus.
You can also register your data management and sharing plan and get a DMP ID to make it a networked or machine actionable DMP (maDMP). The DMP ID will serve as a persistent unique identifier that can be used in your grant application as well as biosketches. The requirements to register your DMP ID include the following:
- Answered at least 50% of questions
- Identified your funder
- Linked your DMPTool account to your ORCID via your Third party applications page
- Plan is not a mock project for testing, practice, or educational purposes
- Once the steps above are satisfied, a button to register your plan will appear in a tab in the Create Plan module called “Finalize/Publish”.
To start writing a plan, please follow the detailed instructions on how to use the DMPTool or watch the WashU DMPTool workshops video recordings and slides below. If you have any further questions or need help, please submit an online consultation request form by selecting the DMPTool.
WashU DMPTool Workshops
- 2023 OVCR Researcher Forum DMPTool Session (1/12/2023): Using the DMPTool to Write an NIH DMS Plan (Slides, Recording)
- 2023 Love Data Week DMPTool Session (2/15/2023): How to Use the WashU DMPTool to Write a Data Management and Sharing Plan (Slides, Recording)
Washington University researchers are encouraged to submit DMS plans that are part of funded grant submissions to the WUSTL Grants Library sponsored by the Institute of Clinical and Translational Sciences. Complete the WUSTL Grants Library Consent Form in order to submit your DMS plan and grant.
Sample DMS Plans
NIH Sample DMS Plans
The following sample Data Management and Sharing Plans (DMSPs) are provided by NIH as examples of how a DMS Plan could be completed in different contexts, conforming to the six elements required in a DMSP according to the 2023 NIH DMS policy (NOT-OD-21-014). 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.
Disclaimer: Some of these NIH sample plans contain language that will not be relevant to all sponsoring institutions. For example, PIs at WashU are responsible for oversight of data management and sharing and complying with the approved DMSP. Therefore, Element 6 of the DMSP should describe how the PI, not WashU’s Office of Sponsored Research Services (OSRS), will monitor and manage the DMSP. Please contact OSRS with any questions.
| Sample | Description | NIH Institute or Center |
|---|---|---|
| Sample Plan 1 | Clinical and/or MRI data from human research participants | NIMH |
Sample Plan 2 | Genomic data from human research participants | NIMH |
| Sample Plan 3 | Genomic data from a non-human source | NIMH |
| Sample Plan 4 | Secondary data analysis | NIMH |
| Sample Plan 5 | Human Genomic data | NHGRI |
| Sample Plan 6 | Technology development | NHGRI |
| Sample Plan 7 | Human clinical and genomics data | NICHD |
| Sample Plan 8 | Gene expression analysis data from non-human model organism (zebrafish) | NICHD |
| Sample Plan 9 | Human survey data | NICHD |
| Sample Plan 10 | Genomic Data from Human Research Participants Examples | NIDDK |
| Sample Plan 11 | Clinical Data from Human Research Participants | NIDDK |
| Sample Plan 12 | Basic Research from a Non-Human Source Example | NIDDK |
| Sample Plan 13 | Secondary Data Analysis Example | NIDDK |
| Sample Plan 14 | Survey and Interview Example | NHGRI |
| Sample Plan 15 | Human Clinical Trial Data | NICHD |
| Sample Plan 16 | Clinical data from human research participants | NIA |
| Sample Plan 17 | Survey, interview, and biological data (tiered access) | NIA |
| Sample Plan 18 | Non-human data (primates) | NIA |
| Sample Plan 19 | Secondary data analysis | NIA |
| Sample Plan 20 | Survey and interview data | NIA |
| Sample Plan 21 | Human clinical and genomic data | NIA |
| Sample Plan 22 | Non-human data (rodents) | NIA |
| Sample Plan 23 | Clinical data (human biospecimens) | NIA |
| Sample Plan 24 | Drug discovery including intellectual property | NIA |
| Sample Plan 25 | HeLa Cell Whole Genome Sequence (DNA or RNA) | OD, NHGRI |
| Sample Plan 26 | Secondary Data Analysis on Data from Human Subjects | NIA |
Example DMS Plans in ICTS WUSTL Grants Library
In collaboration with ICTS and WUSM investigators, the Becker Data Management and Sharing group has gathered DMS plans submitted with grant applications on or after January 25, 2023 for inclusion in the ICTS WUSTL Grants Library. These plans have been reviewed by the Becker DMS staff and selected to be used as example DMS plans to help other WashU investigators when they write a DMS plan for the first time. Example DMS plans will be first deposited into the Submitted folder and then moved to the Awarded folder, so please check back often.
Example DMS Plans by Working Group on NIH DMSP Guidance
- Searchable Catalog of DMPs: The example DMP directory was compiled from researchers, institutions, libraries, and workgroups who shared their data management plans online from 2012-2022. Since the initial launch of this searchable catalog in September 2022, more than twenty new DMS plans using the 2023 NIH DMSP format, including the NIH sample plans, have been added. In addition, the catalog has repository information readily visible in the table. We recommend that you sort the catalog by date in descending order to view the most recent sample plans using the new NIH DMSP format.
- Converting a Resource Sharing Plan into a 2023 NIH DMSP format (Annotated Example DMP in NIH 2023 Format)
Featured DMS Plans in the DMPTool (DMPTool Featured Public Plans)
- Development of Cutibacterium-specific immunoassays to identify true Cutibacterium acnes infections (William Mccoy iv, WashU R03 application for NIAMS, NIH-Default DMSP template, DMP ID: 10.48321/D1WK99): The proposed study generates data from both human samples and non-human sources. All data will be deposited into Digital Commons@Becker and made available via open access for datasets from non-human sources and controlled access for datasets from human samples.
- Effects of Placental Dysfunction on Brain Growth in Congenital Heart Disease (Cynthia Ortinau, WashU R01 application for NICHD, NIH-GEN DMSP (2023) template, DMP ID: 10.48321/D1BS7N) : The proposed study involves human participants and will collect demographic, clinical, MRI, genomic, confocal laser microscopy, and qualitative clinical assessment data. Data will be shared via Digital Commons@Becker (demographic, clinical, qualitative data), OpenNeuro (MRI data) and dbGAP (genomic data).
- Accumbal adaptations that contribute to weight regain after weight loss (Alexxai Kravitz, WashU R01 application for NIDDK, NIH-GEN DSMP (2023) template, DMP ID: 10.48321/D1X324). The proposed study will produce brain recording data, behavioral data and physiological data from mice. All data will be deposited into the Open Science Framework (OSF).
- Using natural language processing to determine predictors of healthy diet and physical activity behavior change in ovarian cancer survivors (Daminian Yukio Romero Diaz, University of Arizona, FASEB DataWorks! Data Management Plan Challenge Winner, DMP ID: 10.48321/D1BK5T)
- FAIR annotated dataset of stroke MRIs, CTs, and metadata (Andreia Faria, Johns Hopkins University, DataWorks!Data Management and Sharing Plan Challenge template, DMP ID: 10.48321/D1J31B)