The Coronavirus Disease Ontology (CovidO)

Sumit Sharma

Keywords: Coronavirus Ontology, Ontology Learning, Semantic Metadata, Semantic Web, Covid-19

TL;DR: In this paper we have introduce a Coronavirus Disease Ontology as a semantic metadata

Abstract: This paper presents the Coronavirus Disease Ontology (CovidO), a superset of the available Coronavirus (Covid-19) ontologies, including all the possible dimensions. CovidO consists of an ontological network of thriving distinct dimensions for storing coronavirus information. CovidO has 175 classes, 169 properties, 4141 triples, 645 individuals with 264 nodes and 308 edges. CovidO is based on standard input of coronavirus disease data sources, activities, and related sources, which collects and validates records for decision-making used to set guidelines and recommend resources. We present CovidO to a growing community of artificial intelligence project developers as pure metadata and illustrate its importance, quality, and impact. The ontology developed in this work addresses grouping the existing ontologies to build a global data model.