Making Lab Data Findable: The “F” in FAIR Data Principles
In 2016, a group of researchers introduced the FAIR Data Principles for scientific data management and stewardship — guidelines to make scientific data Findable, Accessible, Interoperable, and Reusable. FAIR isn’t a single standard or technology. It’s a framework that helps organizations ensure their data can be located, understood, shared securely, and reused by both humans and machines.
As data volumes grow and collaborations span labs, disciplines, and geographies, adopting FAIR has become essential for accelerating discovery, improving compliance, and getting more value from data. In this series of posts, we’ll describe each of the four FAIR components and their underlying principles — starting with Findable — and how extending a traditional LIMS or implementing a new generation of LIMS can help labs implement FAIR data.
