Introduction to RDM and FAIR data

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RDM or Research Data Management RDM is an essential component of responsible and efficient scientific practice. It encompasses the entire lifecycle of research data from planning and collection to documentation, preservation, and sharing. Effective RDM ensures data quality, security, and long term availability, while enabling researchers to organize their work, comply with funder requirements, and enhance the visibility and impact of their research outputs. PINDARE provides guidances, tools, and resources to support researchers in implementing these good practices across all stages of data management.

A central element of modern RDM is the adoption of the FAIR principles, which aim to make data Findable, Accessible, Interoperable, and Reusable. These principles, promoted notably by the European Commission, emphasize the use of persistent identifiers, rich metadata, open and standardized communication protocols, shared vocabularies, and clear licensing and provenance information. By following the FAIR principles, researchers increase the discoverability, transparency, and reusability of their datasets, strengthening collaboration and supporting a more open and sustainable scientific ecosystem.

In this section you will get more details on FAIR data principles and Research Data Management. You can also use the Compass to Research Data Management tool to grasp what attention points are important for your data management.

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