1. Data Types | 2. Related Tools | 3. Standards | 4. Preservation & Access | 5. Restrictions | 6. Oversight

This checklist addresses the 6 required elements which can be found on the Writing a Data Management and Sharing Plan page, in the NIH DMS Policy, and in an optional format worksheet, all from NIH.
*There may be some slight differences between these sources.

Links below take you to more guidance and examples from this website and NIH.

1. Data Type

Summarize the type(s) of scientific data you expect to collect or generate that will be necessary to validate your findings.

  • List and describe the types of data that will be created or used as part of the study, including:
    • Types of data, file formats, size, and number of files (estimate quantities as necessary).
    • Describe which data from the project will be preserved and the reasoning.
    • The level of aggregation, de-identification, or processing/cleaning that will be done prior to sharing.
    • The source(s) of any secondary data or previously collected data to be used in the project.
  • Describe the metadata and other documentation that will be shared with your data to facilitate interpretation, such as:
For data subject to the GDS Policy:

  • Data types expected to be shared under the GDS Policy should be described in this element. Note that the GDS Policy expects certain types of data to be shared that may not be covered by the DMS Policy’s definition of “scientific data”. For more information on the data types to be shared under the GDS Policy, consult Data Submission and Release Expectations.

2. Related Tools, Software, and/or Code

Identify hardware, software/code or other tools necessary to access or manipulate the shared data.

  • State whether or not specialized software, code/scripts, or hardware are needed.
  • For each tool that is necessary, list:
    • Software version number and operating system, if applicable.
    • Describe how the tool can be accessed (e.g., open source and freely available, generally available for a fee in the marketplace, or available only from the research team or some other source). For instance, see sharing code.
    • How long they will be available (if known).

3. Standards

List the standards that will be used for sharing the data and metadata. These may range from open file formats for data, to standards or commonly accepted practices for the structure and organization of documentation (metadata).

Describe and state whether or not there are standards or commonly accepted practices for your field that are applicable:

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:
    1. Does the Funding Opportunity specify a repository?
    2. Does the Institute or Center specify certain repository(ies)?

Selecting a repository: see the NIH Guide, NIH Domain-Specific Repositories, and UI Guide.

If no domain repository exists, we strongly recommend using Iowa Research Online over other generalist repositories.

  • 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).
  • If the repository(ies) has/have particular metadata standards (not usually described), list in the standards section.
  • Revisit your data list from section 1 and
    • Describe when each of the types of data from Section 1 will be made available (portions of the data may be released at different times). Either:
      • Data will be made available when the work is published or the award/support period ends (whichever comes first)
        – OR –
      • Data will be made available earlier
  • State the minimum number of years data will be available, based on repository policies.
For data subject to the GDS Policy:

  • For human genomic data:
  • For non-human genomic data:
    • Investigators may submit data to any widely used repository.
    • Non-human genomic data is expected to be shared as soon as possible, but no later than the time of an associated publication, or end of the performance period, whichever is first.

5. Access, Distribution, or Reuse Considerations

Describe how sharing will be maximized while respecting restrictions.

  • Is there a license you will use (check with the repository for options) to enable or restrict reuse and redistribution? For instance, in IRO we recommend ODC-BY v 1.0 for data.
  • Describe any considerations that may affect the extent of data sharing:
    • Legal (e.g., licenses, intellectual property)
    • Technical considerations or limitations
    • Ethical (e.g., protecting human subjects)
  • Rather than refraining from sharing altogether, consider whether data can be shared with access controls or via a data use agreement. If there are intellectual property concerns, consider if an embargo period would suffice.
  • If you have human subject data, describe how you will protect the privacy, rights, and confidentiality of study participants (de-identification, etc.).
Expectations for human genomic data subject to the GDS Policy:

  • Informed Consent Expectations:
    • For research involving the generation of large-scale human genomic data from cell lines or clinical specimens that were created or collected AFTER the effective date of the GDS Policy (January 25, 2015):
      • NIH expects that informed consent for future research use and broad data sharing will have been obtained. This expectation applies to de-identified cell lines or clinical specimens regardless of whether the data meet technical and/or legal definitions of de-identified (i.e. the research does not meet the definition of “human subjects research” under the Common Rule).
    • For research involving the generation of large-scale human genomic data from cell lines or clinical specimens that were created or collected BEFORE the effective date of the GDS Policy:
      • There may or may not have been consent for research use and broad data sharing. NIH will accept data derived from de-identified cell lines or clinical specimens lacking consent for research use that were created or collected before the effective date of this Policy.
  • Institutional Certifications and Data Sharing Limitation Expectations:
    • DMS Plans should address limitations on sharing by anticipating sharing according to the criteria of the Institutional Certification.
    • In cases where it is anticipated that Institutional Certification criteria cannot be met (i.e., data cannot be shared as expected by the GDS Policy), investigators should state the institutional Certification criteria in their DMS Plan, explaining why the element cannot be met, and indicating what data, if any, can be shared and how to enable sharing to the maximal extent possible (for example, sharing data in a summary format). In some instances, the funding NIH ICO may need to determine whether to grant an exception to the data submission expectation under the GDS Policy.
  • Genomic Summary Results:
    • Investigators conducting research subject to the GDS Policy should indicate in their DMS Plan if a study should be designated as “sensitive” for the purposes of access to Genomic Summary Results (GSR), as described in NOT-OD-19-023.

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.).

This checklist based on one created by the NIH DMSP Guidance for Data Support Services Working Group, with modifications and additional links by Brian Westra.