We have begun drafting documents for supporting researchers at the Hutch in response to the NIH Data Sharing Policy. We took comments/feedback/input from across the Fred Hutch community during October and November of 2022. Moving forward, the Fred Hutch Data Science Lab will continue to maintain and periodically update the resulting support materials for investigators developing NIH DSMP plans. In an attempt to catch people where they are, we will be creating a home for these materials here in SciWiki, on our site’s NIH Data Sharing project page, and in our future CenterNet page. Keep checking back for updates, as this entire policy and the scientific community’s response to it will likely evolve over 2023 and beyond.
We are always open for feedback, corrections and contributions from the Fred Hutch community and beyond. If you like these materials and use them, let us know! If you have developed a great plan and want to share it with us, please do! If you have other feed back about our evolving support materials or the guide, we want to hear it. You can contact us by emailing
We have created and are actively developing a guide you can find here that walks you through the process of complying with the new 2023 NIH Data Sharing Policy.
If you take this course and want to give us feedback or would like to learn more about it, you can share your thoughts in the FH Data Slack in the #ask-dasl channel) or you can file an issue on the course’s GitHub repository or email us at
We’re actively working on improving and editing these documents as well as building a “Mad Libs” style template document for everyone to leverage. If you’d like to contribute to the Mad Libs template, you can provide example text using our Google Form. The more the merrier!
What you should know about the new 2023 NIH Data Management and Sharing Policy
Starting January 25th, 2023, the NIH will implement a new policy that requires new grant applications or renewals that generate scientific data to include a detailed data management and sharing plan. The NIH expects all shareable data to be made available, whether it is associated with a publication or not. The goals of this new policy are to establish the expectation for the management and sharing of scientific data generated from NIH-funded or conducted research, and to emphasize the importance of good data management practices.
Why is the NIH doing this? There are several reasons why sharing data can be beneficial to the scientific community.
The major requirement of the policy is that all grant proposals (submitted after January 25th, 2023) for mechanisms that require compliance, must include a plan for how they will manage and share their data.
For certain grant mechanisms for projects that do not generate data, compliance with the policy is not required. For certain types of data, sharing is not possible, and a justification will be required instead.
What grant mechanisms require compliance with the DMS policy?
The DMS Policy applies to all research that generates scientific data, including:
The DMS Policy does not apply to research and other activities that do not generate scientific data, including:
To determine if your research requires compliance with other policies that may influence how you share your data, take this quiz.
Does my research generate scientific data?
The NIH Data Management and Sharing (DMS) Policy applies to all NIH-supported research generating scientific data. But what is considered “scientific data”?
Scientific data are the “recorded factual material of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications”. This can include any of the following if they are applicable to your study:
You are not expected to share:
We outline these essential components in more depth in our DaSL developed resources described below, however there are 6 elements that will be required in your data management plan.
Dataverse has basic best practices guidance for data management plans.
DMPTool from University of California
Stanford University Library includes some sample DMPs from NIH and other resources.
FAIRSharing policies: A catalogue of data preservation, management and sharing policies form international funding agencies, regulators and journals.