This includes all NIH-supported research regardless of funding level, including: extramural grants, extramural contracts, intramural research projects, and other funding agreements.
Scientific Data is defined as data 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 includes any data needed to validate and replicate research findings.
- Scientific data does 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.
|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:|
The effective date for the DMS Policy is January 25, 2023. Specifically, the policy applies to:
Other policies and expectations may apply (see NIH Institute and Center Data Sharing Policies).
The NIH does not specify data content, formatting, presentation, or transport mode. There are no standards or best practices. The method you choose may depend on several factors, including the sensitivity of your data, its size and complexity, and the volume of requests anticipated.
There are three methods for sharing data:
Regardless of the method used to share data, datasets will require documentation which gives information about the methodology and procedures used to collect the data, details about codes, definitions of variables, variable field locations, frequencies, etc. For more information see Data Standards and Common Data Elements Resource Guide.
Data would need to be shared when your work is published, or before your performance period ends, whichever comes first. In general, you should make your data accessible as soon as possible. You can also use relevant requirements and expectations such as data repository policies, award record retention requirements, or journal policies, to decide when to share your data sets.
NIH expects that researchers will take steps to maximize scientific data sharing, but may acknowledge in Plans that certain factors (i.e., ethical, legal, or technical) may necessitate limiting sharing to some extent. Some of these to-be-expected limitations should be described in Data Management and Sharing Plans. Compelling rationale for limiting scientific data sharing should be provided and will be assessed by NIH. Potential examples of justifiable factors include:
Examples of reasons that would generally not be justifiable factors limiting scientific data sharing include:
NIH respects and recognizes Tribal sovereignty and American Indian and Alaska Native (AI/AN) communities’ data sharing concerns, and NIH has proposed additional considerations when with working with Tribes in the draft supplemental information on “Responsible Management and Sharing of AI/AN Participant Data.”