Data management refers to the process of defining, organizing, and storing data resulting from research projects. The goal is to make the data discoverable and re-usable by other researchers. This increases the value of research to the academic community and improves the return on investment for organizations supporting researchers.
Internationally governments and academic institutions are creating standards and a common practice for data management. Here's one example:
Research Data Management (RDM) efforts in UAE public university libraries.
Research Data Management: A review of UAE academic library experience (degruyter.com)
Funding agencies want to assure that funded research data as well as the results are available for further research. NSF (National Science Foundation in the US) began to mandate Data Management Plans (DMPs) in funding proposals in 2011. Applicants for funding must describe their plans regarding research data retention and access. Other funding agencies have implemented similar requirements. Lately there is a move to assure that the research is also reproducible.
Librarians have expanded their role in information preservation and access to include research data, and many offer assistance as needed.
NSF data management plan requirements
DataQ is a collaborative platform for answering questions about research data in academic libraries. Topics include repositories, data management plans, and grant writing, among others.
DataQ
