What is Research Data Management?
Research data management concerns the organisation of data, from the very start with your research question to the archiving of valuable results and publishing them.
Research Data Management is part of the research process, and aims to make the research process as efficient as possible, and meet expectations and requirements of the university, research funders, and legislation.
It concerns how you:
- Re-use and/or create data and plan for its use,
- Organise, structure, and name data,
- Store it – make it secure, provide access, store and back it up,
- Share with collaborators and more broadly, publish and get cited.
As a whole the University works towards open science as a standard. For research data and all academic output this means that they should meet the FAIR principles:
- Findable: easy to find for both humans and computers, with metadata that facilitate searching for specific datasets,
- Accessible: stored for long term so that they can easily be accessed and/or downloaded with well-defined license and access conditions (open access when possible), whether at the level of metadata, or at the level of the actual data,
- Interoperable: ready to be combined with other datasets by humans or computers,
- Reusable: ready to be used for future research and to be further processed using computational methods.