The focus is applying Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles so that science data can drive innovations in AI. The FAIR principles were originally proposed and endorsed in 2016 by an international collaboration of universities, industry, funding agencies, and scholarly publishers.