A deluge in digital data, the trend for cross-disciplinary and multi-modal scientific investigations along with the tremendous computing power now available, has led to team based, data-driven and data-intensive methods commonly used in science. These advances also come with a set of challenges summarized in the FAIR (1) guiding principles for research data management – make heterogeneous data generated from different contexts, Findable, Accessible, Interoperable and Reusable. Accordingly, Knowledge Graphs have become the go-to key solution across both research and industry to address these challenges.