Middle-Out FAIR Data Integration with Knowledge Graphs
Knowledge Graph Conference 2020
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18m
An extremely powerful and efficient use for Knowledge Graphs is to unite well-understood domains of knowledge alongside novel and specific business/scientific questions. Using small ontologies that embed large reference taxonomies, we are able to go from tactical scientific questions (bottom-up) to common taxonomies and reference datasets (middle-out) approach to model scientific questions, aligning with enterprise master data strategies on the way up. If building blocks follow FAIR (Findable, Accessible, Interoperable, Reusable) data principles, reusing these processes becomes more and more efficient over time as the middle layer grows. Examples in the translational medicine space will be highlighted.
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