Developing Scientific Knowledge Graphs Using Whyis

Abstract

We present Whyis, the first framework for creating custom provenance-driven knowledge graphs. Whyis knowledge graphs are based on nanopublications, which simplifies and standardizes the production of structured, provenance-supported knowledge in knowledge graphs. To demonstrate Whyis, we created BioKG, a probabilistic biology knowledge graph, and populated it with well-used drug and protein content from DrugBank, Uniprot, and OBO Foundry ontologies. As shown with BioKG, knowledge graph developers can use Whyis to configure custom knowledge curation pipelines using data importers and semantic extract, transform, and load scripts. Whyis also contains a knowledge metaanalysis capability for use in customizable graph exploration. The flexible, nanopublication-based architecture of Whyis lets knowledge graph developers integrate, extend, and publish knowledge from heterogeneous sources on the web.