COVIDKG.ORG - a Web-scale COVID-19 Interactive, Trustworthy Knowledge Graph, Constructed and Interrogated for Bias using Deep-Learning

Abstract

We describe a Web-scale interactive Knowledge Graph (KG) , populated with trustworthy information from the latest published medical findings on COVID-19. Currently existing, socially maintained KGs, such as YAGO or DBPedia or more specialized medical ontologies, such as NCBI, Virus-, and COVID-19-related are getting stale very quickly, lack any latest COVID-19 medical findings - most importantly lack any scalable mechanism to keep them up to date. Here we describe COVIDKG.ORG - an online, interactive, trust-worthy COVID-19 Web-scale Knowledge Graph and several advanced search-engines. Its content is extracted and updated from the latest medical research. Because of that it does not suffer from any bias or misinformation, often dominating public information sources.