Fig. 6: Vision of CKG’s deployment.
From: A knowledge graph to interpret clinical proteomics data
a, Reports and notebooks in local graphs can readily be shared to replicate analyses, thereby contributing to reproducible science. b, Aggregating data and knowledge of multiple projects from different groups within a community would allow direct and deep project comparison and lead to increasingly more robust and powerful analysis and knowledge generation. c, To protect the sensitive nature of healthcare data and still allow researchers to train models and learn from the data, the CKG could be implemented as a protected graph using federated learning. EHR, electronic health record.
