Research data, according to the federal government, refers to “the recorded factual material commonly accepted in the scientific community as necessary to validate research findings.” It can exist in various forms, depending on the discipline and research topic. For example, research data can be:
Research data management and sharing consists of actions researchers take to plan, acquire, store, process, analyze, preserve, share, find, and reuse research data for their projects. It involves how researchers handle their data (e.g., using consistent naming conventions to facilitate organization and retrieval of files) and what researchers decide to do with the data upon completion of their projects (e.g., depositing research data in an online repository for access, reuse, and preservation).
Research data management and sharing can be presented as a lifecycle because sharing research data enables reuse, supports reproducibility, and facilitates the creation of another research project. Below is one rendition of the research data lifecycle.
Research data management and sharing presented as a lifecycle by Princeton University.
Research data management and sharing brings about a variety of benefits, including but not limited to:
Effective data management and sharing starts with preparing a well-thought-out plan and adopting recommended practices in the research process. Cornell University has compiled a glossary that explains relevant terms in plain language. If you have any questions, feel free to contact the Center for Digital Scholarship.