CODO: An Ontology for Collection and Analysis of Covid-19 Data
This provides a standards-based model for researchers and organizations to unify COVID-19 data, but it is incremental as it builds on existing vocabularies and practices.
The authors tackled the problem of integrating heterogeneous COVID-19 data sources by developing CODO, an ontology that facilitates data collection and analysis, and it has been used with real-world data from the government of India.
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 heterogeneous 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.