Data Management: Data Management Plans & Grants

A data management plan, or DMP for short, is a document in which a researcher or research team outlines a plan for the data their project will produce. Some funders require data management plans as part of the submission process. DMPs typically address questions such as:

• What types of data will be created?
• How, when, and who will do the work?
• Who will own, have access to, and be responsible for managing these data?
• What equipment and methods will be used to capture and process data?
• Will data be reviewed for quality?
• Where will data be stored during and after?

The U.K Digital Curation Centre's Checklist for a Data Management Plan can help get started thinking about the elements of a thorough DMP.

It is best to check with the specific funding agency or publisher directly to be certain you are following the most recent guidelines. SPARC tracks data sharing policies by federal departments that researchers can use. 

NIH Data Guidelines

The National Institute of Health released an updated Data Management and Sharing Policy in 2023. Under this, researchers are required to submit a Data Management and Sharing (DMS) plan with their grant applications. As part of this, they're expected to discuss how they will manage and publicly share their data outputs. Here are some things to keep in mind:

• The new policy covers scientific data that's part of research projects and some other projects as well, but not all data types are considered scientific data. See the NIH's policy on what's covered for more information.
• The DMS should be succinct - two pages or less - but clearly address each component of the plan. Avoid filler language or redundancy. If you use the DMPTool and select the NIH template, you will receive guidance on how to address each section along with sample language.
• Checkout the NIH's how to write a DMS guide.
• It's not enough to just share data - the NIH expects researchers to also provide enough context about how to use the data, including the methodology used to collect the data, definitions for all variables, and code used to manipulate data, to allow others the ability to competently use the data as well.
• Data from NIH-funded projects should be shared either when related outputs are published or at the end of the performance period, whichever is earlier.
• The NIH does not have a preferred data repository, although it does have a list of acceptable generalist repositories as well as NIH-related repositories.
• The University has an institutional subscription to Dryad, one of the approved general data repositories, that anyone at UNR may use free of charge. 
• Dryad is not suitable for all data, however, such as data protected by copyright. For those datasets that cannot be shared through Dryad, researchers can consider the University's institutional repository, ScholarWolf. Contact Librarian Teresa Schultz at teresas@unr.edu if you have questions.