What is research data management?
Research data management (RDM) concerns the careful handling and organization of research data throughout the entire research lifecycle with the aim to carry out research activities efficiently and allow collaboration with others.
More specifically, RDM aims:
- to protect research data against loss;
- to enable sharing of research data with others
- to make research data discoverable, accessible and (re)usable
Protecting Research Data
RDM begins with protection of the research data. Data protection has two aspects:
- data safety, this is to protect against data loss through storage (including backups) and archiving, and by good organization and documentation;
- data security, this is protection of data against unwanted changes, which can be achieved by controlling access to data;
- data organization, protecting data from untraceability by systematic data arrangemen
Sharing Research Data
A core principle in RDM is sharing research data with others. Research data will be shared with others for two reasons:
Making Data FAIR
Adequate sharing of research data for reuse presupposes that data are findable, accessible, interoperable and reusable. These requirements are known as the FAIR principles for research data.
- More information on the FAIR making data usable.
“Before being re-usable, your data have first to be usable”