Generally, research data management (RDM) is the management of data used or generated during a research project. It is an essential part of the research process and helps to ensure that your data is properly organized, described, preserved, and shared.

Whether you are an undergraduate, graduate, staff, or faculty researcher, practicing good RDM skills is one of the best ways to ensure the standardization and reproducibility of your data. Additionally, managing your data well now will save you time and frustration in the long run.

Created by DataOne, the below image is a pictorial representation of the stages involved in the successful management of research data. DataOne's research data lifecycle includes eight components: Plan, Collect, Assure, Describe, Preserve, Discover, Integrate, and Analyze. It begins at the top with Plan and moves clockwise through the process. After your research project is planned, your data are then collected and assured through quality control. Data are then described following metadata standards and then preserved in a long-term archive. Potentially relevant data are discovered and can be integrated to form one set of similar data that can then be analyzed.

This data lifecycle is designed to be discipline agnostic but it is important to note that your research activity may not utilize every part of this data lifecycle.