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    Data Management and Sharing Plan (DMSP)

    The first branch of the Data Management Trifecta is the creation of the data management and sharing plan to submit with the grant proposal. The plan describes how the project's scientific data will be collected, processed / analyzed, and shared. Please note that the plan pertains to scientific data only.

    UConn Health has adopted the DMPTool to aid in the creation of the DMSP.   Users must sign up with a UConn Health email address ( to access the custom template.

    Please note:

    • Principal Investigators (PIs) are at liberty to author new plans, work off an existing template, or use the DMPTool to develop their DMSPs.
    • The DMSP and Resource Sharing Plan are separate attachments that may be required for your application; one does not necessarily replace the other. Read the NIH article about the DMSP vs. Resource Planning.

    The DMPTool

    The DMPTool is a free, open-source, online tool that provides a click-through wizard for creating an NIH-compliant DMSP.  To facilitate the creation of the DMSPs, we have adopted and customized the DMPTool for UConn Health researchers.   The template incorporates links to information that will help you craft the plan and allows users to collaborate with colleagues inside and outside of their institution. 

    For projects that are similar to a previous one, the tool provides the ability for researchers to copy and modify an existing plan for use with a new project, if needed. The tool also provides a quantity of publicly available plans, on a variety of research topics, or reference purposes.

    To help you get started, we created these step-by-step training videos:

    Also, please consult this brief step-by-step Quick Start Guide.


    What Is Scientific Data?

    According to the NIH, "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 Six Elements of the Plan

    Although the plan can take any shape or form, the NIH recommends that the plan not exceed two pages and must address these six basic elements:

    1. Data Types: Types, estimated volume, and details about shared data, metadata, and other documentation.
    2. Preservation, Access, Timeliness: Repositories, FAIR protocols, timelines for data availability and retention.
    3. Standards: Name(s) and application(s) of data and metadata standards that will be applied.
    4. Access, Distribution, or Reuse Considerations: Factors, controls, and protections affecting access and use.
    5. Related Tools, Software, and Code: Specialized tools, software, code required for access and handling.
    6. Oversight: The person(s) responsible to monitor and manage compliance with the plan

      Data Sharing Considerations

      The NIH recognizes justifiable ethical, legal, technical factors for limited sharing, including when:

      • Informed consent will not permit or limits scope of sharing or use.
      • The privacy or safety of research participants is compromised.
      • Federal, state, local, or tribal law, regulations, or policy prohibits disclosure. e.g., HIPAA
      • Data is collected from human participants; there may be additional considerations.

      Researchers should consider requirements and expectations across disciplines for appropriate time frames, and:

      • Data repository and Journal policies
      • Funder/Award requirements: retention, repositories, etc.
      • Data downloaded from public repositories are not expected to be shared again.

      The data should be shared as soon as possible, but no later than the time of a publication of findings in a peer-reviewed journal OR at the end of the award, whichever comes first.

        Additional Considerations for Human Data

        As listed on the NIH website

        When working with human participant data, including de-identified human data, here are some additional characteristics to
        look for:

        • Fidelity to Consent: Uses documented procedures to restrict dataset access and use to those that are consistent with
          participant consent and changes in consent.
        • Restricted Use Compliant: Uses documented procedures to communicate and enforce data use restrictions, such as
          preventing reidentification or redistribution to unauthorized users.
        • Privacy: Implements and provides documentation of measures (for example, tiered access, credentialing of data users,
          security safeguards against potential breaches) to protect human subjects’ data from inappropriate access.
        • Plan for Breach: Has security measures that include a response plan for detected data breaches.
        • Download Control: Controls and audits access to and download of datasets (if download is permitted).
        • Violations: Has procedures for addressing violations of terms-of-use by users and data mismanagement by the
        • Request Review: Makes use of an established and transparent process for reviewing data access requests