What is Research Data Management (RDM)?

Research Data Management (RDM) is encompasses the processes applied throughout the lifecycle of a research project to guide the collection, documentation, storage, sharing, and preservation of research data, and allows researchers to find and access data.

project lifecycle represented by a orange circle with icons for plan, create, process, analyze, disseminate, preserve, and reuse.

This is process is usually formalized in a data management plan (DMP). A Data Management Plan is built around the particular needs of each project, but there are concepts and considerations in building the plan are similar across projects. Typically sections of a DMP include, but is not limited to,:

  • Data collection
  • Documentation and metadata
  • Storage and backup
  • Preservation
  • Sharing and reuse
  • Responsibilities and resources
  • Ethics and legal compliance

Why Manage your Research Data?

  • meet funding agency requirements
  • write more competitive grant applications
  • get credit for your data and increase its impact and visibility
  • encourage the discovery and use of your data to explore new research questions
  • improve your data's accuracy, completeness, and usability
  • ensure long-term preservation of data for future researchers
  • comply with ethics and privacy policies

Watch a data management horror story created by the NYU Health Sciences Library below.

Adapted from Research Data Management @ Queen's University Library Guide and Digital Research Alliance  of Canada, Research Data Repositories 101 – Module 2,  CC BY-NC 4.0