When FAIR Becomes Architecture: Solving Preclinical Data Fragmentation at Scale

How Graphwise helped a top-5 global pharmaceutical company transform a fragmented preclinical in vivo data landscape into a coherent, semantically rich and queryable knowledge graph by engineering a production platform with FAIR principles built into every layer of its architecture. The FAIR data principles — Findable, Accessible, Interoperable, Reusable — have become a widely accepted framework for research data management. But articulating the principles is the easy part. Engineering a production platform that embeds them into every layer of the architecture is a different challenge entire..