Despite the existence of vast amounts of biomedical data, these remain difficult to find and to productively reuse in machine learning and other Artificial Intelligence technologies. In this talk, I will discuss the role of the FAIR Guiding Principles to make AI-ready biomedical data, and their representation as knowledge graphs not only enables powerful ontology-backed semantic queries, but also can be used to predict missing information, as well as to check the quality of knowledge collected.

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