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Research Data Management

Make informed choices for research data. RDM, policy, practical guidelines, software and tools at VU Amsterdam. FAIR data, archiving, storage, publication

What is Research Data Management?

Research data management (RDM) concerns the organisation, documentation, storage, archiving and sharing of digital and analogue data. Data management applies throughout the entire research data life cycle, which is visualised in the circle above. RDM aims to ensure reliable verification of results, and permits new and innovative research built on existing information. RDM is also part of the research process and is intended to make the research process as efficient as possible. This LibGuide provides guidance on research data management planning, data storage and protection, data archiving, and other resources. The Data Management Plan provides information on how these activities will be carried out during the research project.

Good data management will heighten the quality of your own research (data) as well as your institution’s scientific output, and it contributes significantly to your field as a whole.
Good data management:

  • Promotes the integrity of your research,
  • Increases the impact of your research,
  • Improves the quality of your data,
  • Supports future use of your research data, and
  • Complies with internal and external regulations.

FAIR principles

The purpose of good data documentation is to facilitate knowledge exchange. The FAIR principles are the guidelines for every form of research output, and in making data available to others.
Every research group should apply these principles when structuring and preserving their data or other research outputs. Making data FAIR involves many aspects of data collection, organization, availability and storage. FAIR does not mean open or public, it means that there is documentation about how access to the data can be achieved.
More information:
Wilkinson, M. D., M. Dumontier, I. J. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship; Scientific Data 3 (1): 160018.