The COviD-19 Ontology for cases and patient information (CODO) provides a model for the collection and analysis of data about the COVID-19 pandemic. The ontology provides a standards-based open source model that facilitates the integration of data from heterogenous data sources. The ontology was designed by analysing disparate COVID-19 data sources such as datasets, literature, services, etc. The ontology follows the best practices for vocabularies by re-using concepts from other leading vocabularies and by using the W3C standards RDF, OWL, SWRL, and SPARQL. The ontology already has one independent user and has incorporated real world data from the government of India. a https://sites.google.com/site/dutta2005/home b https://www.michaeldebellis.com/ Dutta, B. and DeBellis, M. (2020). CODO: an ontology for collection and analysis of COVID-19 data. Accepted for publication in the Proc. of 12 th Int. Conf. on Knowledge Engineering and Ontology Development (KEOD), 2-4 November 2020.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.