FAIR Research Data Management – What is FAIR RDM and why should we do it?
From The Embassy of Good Science
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FAIR Research Data Management – What is FAIR RDM and why should we do it?
Related Initiative
What is this about?
This training introduces the concept of FAIR Research Data Management (RDM) and explains what the FAIR principles Findable, Accessible, Interoperable, and Reusable mean in practice for researchers. It provides an overview of why research data management matters and how FAIR principles support good scientific practice throughout the research lifecycle. The training clarifies the relationship between FAIR data, open data, and managed data, highlighting common misunderstandings. Through practical examples, short exercises, and quizzes, participants learn how research data can be made more reusable for both humans and machines. The course is designed for researchers and research support staff who want a foundational understanding of FAIR RDM and how it contributes to transparency, collaboration, and long-term value of research outputs.
Why is this important?
FAIR Research Data Management is essential for improving the quality, visibility, and impact of research. By applying FAIR principles, researchers ensure that their data can be easily discovered, accessed, understood, and reused by others, including future researchers and automated systems. This reduces duplication of effort, increases research transparency, and supports reproducibility. FAIR RDM also aligns with funder, institutional, and policy requirements, helping researchers meet compliance standards. Ultimately, it maximizes the value of research investments and enables data-driven innovation across disciplines and borders.
