NIH Data Management and Sharing Plan Checklist

NIH Data Management and Sharing Plan Checklist

This DMS plan checklist addresses the required elements of the NIH DMS policy, which is effective January 25, 2023 for all grant proposals. 

 Check the guidance for the grant you are applying to for more specific requirements beyond the general NIH policy. 
  Check for more specific data policies from Institutes, Centers, and Offices (ICOS)
 Track the plan elements that can be included in the grant budget
  Getting help with your plan:
You can get help on your DMP during our office hours. See our Spring 2023 Office Hours for NIH DMS Plans page for dates and times.
 You may also use the NIH template in DMPTool to draft your answers to the following questions and request feedback from an RDS consultant. If requesting feedback from a RDS consultant through DMPTool, please allow as much lead time as possible and email if the review needs to be expedited. (DMPTool cannot submit your plan directly to your funder so you will need to download it and send the PDF with the rest of your materials.

1. Data Type

Summarize the scientific data you expect to collect or generate that will be necessary to validate your findings.
 List or create a table to describe the datasets that will be created or used as part of the study, including:
 Data type, format, size, and number of files along with estimated sizes/quantities
 Which datasets will be shared and rationale.
 The level of aggregation, de-identification, or processing/cleaning that will be done prior to sharing.
 The source of any secondary data, previously collected data reused in this project.
 List the metadata and other documentation (e.g. a README file)  that will be shared with your data to facilitate interpretation. 

2. Related Tools, Software, and/or Code

Identify tools, software, hardware, and/or code necessary to access or manipulate the shared data.
 State whether or not specialized tools are necessary.
 For each tool that is needed, list:
 Version number and operating system,
 How the tool can be accessed – whether it is open source and freely available, generally available for a fee in the marketplace, or available only from the research team or another source, or whether the tool has to be reconstructed using code. 
 How long the tool will be available if it is known.

3. Standards

List the standards that will be used for sharing the data and metadata
 State and describe data standards for your field that are applicable to your project. If there are no standards that apply, list how you are describing your data and recording it.  

Typical data standards include:

  • Metadata schemas
  • Standard Terminologies (Controlled Vocabulary andOntologies)
  • Content/ Encoding Standards
  • Common Data Elements
  • Identifiers (PIDs)

4. Data Preservation, Access, and Associated Timelines

Provide details and timelines for sharing and preserving data for long term usability.
 Name the repository(ies) where data will be archived:

  • If a particular metadata standard is required, list in the standards section.
  • Check the funding announcement to see if a specific NIH repository may be required. If there isn’t, a disciplinary, generalist, or institutional repository may also be options.

 Specify which type of unique identifier is used by the repository (DOI, handle, ID number, accession number) (Note- an identifier is not required at time of DMS plan submission).
 Revisit your data list from section 1 and state when the data will be made available (portions of the data may be released at different times). Timelines required by the policy are:

  • Data will be made available when the work is published or the award/support period ends (whichever comes first)
  • Data will be made available earlier.

 State the minimum number of years data will be available, based on repository policies. The UW Data Stewardship and Retention policy requires that data be archived for a minimum of 7 years after the final project closeout. 

5. Access, Distribution, or Reuse Considerations

Describe how sharing will be maximized while respecting restrictions.
 Describe any considerations that may affect the extent of data sharing:

  • Legal (Ex: copyright, intellectual property)
  • Technical
  • Ethical

 Consider the possibility of sharing data with access controls, or whether an embargo period might be a solution to intellectual property concerns rather than refraining from sharing altogether. 
 If you have human subjects data, describe how you will protect the privacy, rights, and confidentiality of study participants (de-identification, etc.).

6. Oversight of Data Management and Sharing

Identify who will be responsible for plan compliance and oversight.

 List names and titles/roles of everyone who will be responsible for monitoring compliance with the data management plan and updating it as needed.
 State how often compliance with the data management plan will be verified (e.g. every ___ months, on the first of each month, etc.). Updates will be required during regular process reporting. 


This checklist was created by the NIH DMSP Guidance for Data Support Services Working Group  with modification by UW-Madison Research Data Services.