AI-Ready Reference Data Architecture
KGC 2026
•
17m
https://drive.google.com/file/d/1xpWLwHlekc3W5s-nRVvMz7Qxz_mmjV2v/view?usp=share_link
This talk will share how LifeScience Companies have moved from a fragmented reference data architecture, where meaning is recreated in every system and pipeline, to an authoritative context architecture, where meaning is created once, governed, and reused everywhere for many use cases.
Open standards knowledge graph using the TopQuadrant platform is implemented to govern, normalize, and publish semantic data products that are AI-ready. A reference data layer is the arbiter of "authoritative context” in order to advance on-demand patient-centric vision and end-to-end business value across R&D, Commercial, and Supply Chain functions.
Companies such as J&J approach to building and governing a multi-graph architecture organizes itself around the concept of a “semantic system of record,” where an enterprise semantic layer ensures that diverse knowledge graphs—from disease and research graphs to runtime and application-specific graphs—“speak the same language” to enable consistent, high-quality data products across the organization.
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