A Data Management Plan (DMP) describes your data, how you will treat your data during your project, and what happens with your data when the project ends. DMPs should touch on the entire data life cycle—from data discovery/collection, to organization, documentation and storage, and finally to preservation and sharing. Think of a DMP as both a required document for grants and a living document for your research planning process.
Typical Pieces of a Good Data Management Plan:
- Types of data used, in detail, and how it was collected
- Detailed metadata standards and supporting documents from Cornell, even by discipline
- Clear data policies, ethics, and legal compliance
- Plans for preservation and data sharing, both short-term and long-term
- Resources needed to accomplish data management - personnel, hardware, software, budget
To learn more about Research Data Management, please see our Research Data Management guide (opens in new tab).
Why do I need a DMP?
Formally articulating these things helps you identify weaknesses in your research plan and is a critical component of ensuring that your research is repeatable, replicable, and reproducible. Practically speaking, many funding agencies, including most of the federal government, require a DMP with every funding request. Funders are also increasingly requiring your to share your data (learn more from our Open Data page).
To learn more about Research Data Management and funding requirements, please see our Research Data Management guide (opens in new tab).