COVID19-OBKG: An Ontology-Based Knowledge Graph and Web Service for COVID-19

Given the huge amount of data from diverse sources and involving various conceptual fields in heterogeneous formats, researchers have encountered challenges in their effort to process, search for, and access knowledge about coronavirus disease 2019 (COVID-19). In this paper, we built COVID19-OBKG, an ontology-based knowledge graph and web service for COVID-19, to enable the access and retrieval of knowledge. First, we built the schema of COVID19-OBKG based on biomedical ontologies to guide the construction of the instance layer of COVID19-OBKG from top to bottom. Secondly, we collected data sources related to COVID-19, including structured databases and web pages. We acquired entities and relationships from data sources through named entity recognition and relation extraction algorithms and merged them with knowledge in biomedical ontologies. Thirdly, we modeled our data in the form of an attribute graph and stored it in Dgraph. Finally, we built a web service to support the retrieval and visualization of COVID19-OBKG, which verified the effectiveness of our approach to constructing a knowledge graph, and the usability of COVID19-OBKG.