What is Research Data Management (RDM)?

Research data management (RDM) is the process of organising and documenting data processes (collection, description, de-identification, curation, archiving and publication) within a research project, ideally towards making it FAIR

Data varies across faculties and disciplines, and some research fields by their very nature involve some kind of data literacy due to the software that is needed to do the research. Managing data, however, is something that needs to occur within every research event, in every department. Traditionally, RDM happened tacitly over the course of a researcher’s career. Today, however, managing data is a necessary part of research, yet data management literacy is still in its infancy. 

Working with data is challenging. Professional data management practices can make research more coherent and shareable, which translates to research being relevant and valuable. By using the FAIR principles, researchers can achieve far more efficiency with their data. Importantly, even if a researcher can not make their data completely accessible, practising good research data management helps you make the research more efficient, searchable and findable.