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Research Data

A guide for locating, managing, and sharing research data.

Draft Data Management Plan Template (NIH)

Good Data Management


"Good data management means determining how data will be collected, what that data will look like, where it will live, and who will be responsible for it -- all before the experiment starts -- and then clearly documenting that information."

NYU Langone Health. Research Data Management Training for Information Professionals: Data Documentation Best Practices. Retrieved from https://nyumc.qualtrics.com/jfe/form/SV_e3SWjfWQjuawW6q

 

Writing a Data Management Plan (DMP)

What is a Data Management Plan?


A data management plan (or DMP) is a formal plan that describes how research data are managed throughout the lifecycle of a research project. Planning saves time in the long run by integrating processes within and after the life of a project. It minimizes the need to reorganize, reformat, or attempt to remember details about data when disseminating and sharing with others. Many funding agencies and journals have data management policies and guidelines. 

Adapted from: Portage Network. (2020, August 25). Primer - Data Management Plan. Zenodo. https://doi.org/10.5281/zenodo.4495631 under CC BY-NC-SA 4.0 license

 

 

Suggested Basic Elements of a Data Management and Sharing Plan (From NIH 2023 Policy)


For NIH 2023 Data Sharing and Management Policy, DMPs should typically not to be longer than 2 pages and must be submitted with application for funding in Budget Justification section. The NIH provides a draft template here.

1. Data Type

Briefly describe the scientific data to be managed, preserved, and shared.

2. Related Tools, Software, Code

Tools and software needed to access and manipulate data, and where you can find them.

3. Standards

An indication of what standards will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation). 

4. Data Preservation, Access, Timelines

Repository to be used, persistent identifiers (PID), and when/how long data will be available.

Encourages use of established repositories.

(Note that NIH ICs or journal publishers may designate specific data repositories to be used.)

5. Access, Distribution, and Reuse Considerations

Potential limitations on use, access, distribution. NIH expects that in drafting Plans, researchers maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues.

6. Oversight of Data Management

Indicate how compliance with the Plan will be monitored and managed, frequency of oversight, and by whom (e.g., titles, roles).

Who has primary responsibility for ensuring that:

  • Naming conventions are adhered to
  • Consistent level of detail are captured
  • Access controls are in place
  • Version controls are followed
  • Data are validated
  • Regular backups occur

(Learn more: Supplemental Information to the NIH Policy for Data Management and Sharing - Elements of an NIH Data Management and Sharing Plan)

 

Resources