NIH Data Sharing & Public Access Policies

The Data Management and Sharing Policy requires the submission of a Data Management & Sharing Plan with every NIH grant regardless of funding level. (There are some exceptions, like training, fellowship, conference grants. Also see Which Policies Apply to My Research?) The new NIH policy takes effect for grants submitted on or after January 25, 2023. There are several relevant notices to inform the research community of these changes, first the Final NIH Policy for Data Management and Sharing, and a supplementary notice describing the expected format and sections of the Data Management and Sharing Plans. These sections will be described on this page.

1.) Data Type

2.) Related Tools, Software and/or Code

3.) Standards

4.) Data Preservation, Access, and Associated Timelines

5.) Access, Distribution, or Reuse Considerations

6.) Oversight of Data Management and Sharing

Recommended Tool: 

The DMPTool features a specific template for the NIH DMSP, including recommended language in each section.

This section is broken into three categories.

1.A. What data will be generated or collected during the course of the project?

1.B. What data of the generated/collected will be preserved and shared?

1.C. What documentation will be created to accompany the data and provided alongside it to offer context about the creation and use of the data?

These sections are each described briefly, and as result, this is not a location to reiterate the aims of the project.

Helpful points to include in this section are:

• Types of files that will be generated (spreadsheets, matrices, fasta files, image file types, etc.)
• Estimated amounts of data that will be generated and what of that will be shared
• Data modality (genomic data, imaging data, survey data, etc.)
• Accompanying documentation to provide contexts such as a ReadMe.txt file, code books, study protocols, or a data dictionary (1.C.)

This section will describe the tools, code and software required to facilitate manipulations, access, reproduce and reuse the data.

Helpful points to include in this section:

• Names and versions of software packages used.
• Specify how tools can be accessed (proprietary or open source?)
• Longevity or period of time available, if known. Will it be available as long as the data?

Recommended Resources:

Barker, M., Chue Hong, N.P., Katz, D.S. et al. Introducing the FAIR Principles for research software. Sci Data 9, 622 (2022). https://doi.org/10.1038/s41597-022-01710-x

This section will identify standards that will be applied to the scientific data and metadata. Some examples of standards are:

• Unique persistent identifiers (ORCiD, or Digital Object Identifers).
• Common data elements
• Data formats
• Controlled vocabularies
• Ontologies
• Metadata schema

If no standards exist in the research field, indicate as much in this section. If multiple competing standards exist, select one. The arena of standards is complex and varies greatly among subdisciplines. Do your best to determine if standards exist.

Helpful points to include in this section:

• What standards will you employ in your data sharing?
• What standards are supported by your selected data repository?

Recommended Resources:

This section will include plans and associated timelines for data preservation and access.

Note: "NIH encourages scientific data be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first." Quote from Supplemental Information to the NIH Policy for Data Management and Sharing: Elements of an NIH Data Management and Sharing Plan.

Helpful points to include:

• Name of and brief details about the repository(ies) where data will be deposited for preservation and access
• How the data will be made findable and identifiable (Persistent Unique Identifiers, indexing standards)
• When the data will be shared
• How long will the data remain available (explore longevity plans and retention policies of repositories)

Recommended Resources:

This section will describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:

• Informed consent
• Privacy and confidentiality
• Controlled access to data derived from human subjects
• Any restrictions imposed by federal, Tribal, or state laws, regulations, or policies or anticipated agreements
• Any other considerations that may limit the extent of data sharing

Helpful points to include:

• List the factors that affect subsequent access, distribution, or reuse
• Any measures taken to appropriately control access to sensitive data
• List relevant protections and restrictions imposed by federal, Tribal, or state laws, regulations, or policies

Recommended Resources:

This section will describe how compliance with the DMS Plan will be monitored and managed, the frequency of oversight, and by whim (e.g., title, roles).

Though the PI will ultimately be responsible for the grant, they may delegate responsibilities to others.

Helpful points to include:

• Determine and list responsible parties for your data collection, storage and sharing
• Indicate timelines for the oversight tasks

Recommended resources:

• Consider incorporating a RACI (Responsible, Accountable, Consulted, Informed) Responsibility Assignment Matrix into the lab workflow