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NIH Data Management and Sharing Policy

Guide to Complying With the 2023 NIH Data Management and Sharing Policy

Effective January 25, 2023, the NIH Data Management and Sharing Policy will require: 

  • ALL funding applications or renewals that generate scientific to include a Data Management and Sharing Plan (DMS Plan) 
  • Successful applicants must comply with submitted DMS Plans

NIH Sharing provides resources on the policy and data sharing from the NIH.


What is a DMS Plan? 

A DMS Plan is an approximately 2-page document that outlines how research data will be managed, shared, and disseminated. NIH compliant DMS Plans should be approximately two pages and include information on the following elements: Data Type; Related Tools, Software and/or Code; Standards; Data Preservation, Access and Associated Timelines; Access, Distribution, or Reuse Considerations; and Oversight of Data Management and Sharing. Details on these elements, writing DMSP's, and information a DMSP template tool, DMPTool are available here

Am I required to share my data?

The policy encourages efforts to maximize appropriate sharing, but recognizes exceptions (i.e., legal, ethical, or technical reasons). These reasons must be communicated in the NIH DMS Plan.  In addition, sharing plans must be communicated in informed consent documents. In the end, management processes for ALL data should be described in an NIH DMS Plan, but not all data must be shared.

How does the NIH define scientific data?

Scientific Data are "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."

Why is the NIH making these changes? 

The NIH is emphasizing good data stewardship with the goals of advancing rigorous and reproducible research and promoting public trust in scientific endeavors.