This page is intended to inform research teams about the new NIH policy, linking to appropriate information and resources whenever possible. This page will be updated as new information becomes available. The information is developed with human subjects research and health data research considerations.

Policy Requirements - What's New

Starting January 25, 2023, the National Institutes of Health (NIH) will require all researchers seeking grant funds that result in the generation of scientific data to:

  • Submit a two-page data management and sharing plan as part of the funding application. The plan must outline how their scientific data and accompanying documentation will be managed and shared.

  • Submit a data management and sharing plan as part of the grant application process.

  • Maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research in the plan, with justified limitations or exceptions.

For more details about the new data management and data sharing policy, read the NIH Scientific Data Sharing one page guide: The Who, What, Where and When of the NIH Data Management and Sharing (DMS) Policy (PDF).

A Data Management Plan (DMP)  is a document that outlines best practices in data management and how you will apply these practices in the course of your grant or project.

The following elements must be addressed in your plan:

  • Data Type - Include the type of data and estimated amount of data being generated. Use general terms and descriptions about data modality (e.g. imaging, genomic, mobile, survey), how the data is aggregated and processed.

  • Related Tools, Software and Code - Indicate if specialized tools are needed to reproduce your research and how they can be accessed.

  • Standards - An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).

  • Data Preservation - The name of the repository, where scientific data and metadata will be archived. For more information see NIH Repositories for Sharing Scientific Data.

  • Access and Timelines - A description of how the data will be made available and what unique persistent identifiers (PID) you will use to support reporting out on your progress and outputs. Provide the timeframe with the expectation that the data should be made available as soon as possible.

  • Access, Distribution, or Reuse Considerations - Including informed consent, privacy and confidentiality protections like de-identification and Certificates of Confidentiality, any data use agreements or licensing limitations.

  • Oversight of Data Management and Sharing - How and when the data management plan will be monitored and managed, and by whom (e.g. , titles, roles).

Taken from:

UC San Francisco has created the DMP Template(s). These are based on the NIH format and have sample language to get you started.

The following real world examples relate to health data and demonstrate the value of using a direct object identifier for your plan as well as connecting the DOI to your ORCID. Using the DMP tool to create and manage all your DMPs will help you stay organized.

  • Damian Yukio Romero Diaz. (2022). "Using natural language processing to determine predictors of healthy diet and physical activity behavior change in ovarian cancer survivors" [Data Management Plan]. DMPHub.

  • Andreia Faria. (2022). "FAIR annotated dataset of stroke MRIs, CTs, and metadata" [Data Management Plan]. DMPHub.