CODO: An Ontology for Collection and Analysis of Covid-19 Data

September 02, 2020 Β· Declared Dead Β· πŸ› International Conference on Knowledge Engineering and Ontology Development

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Authors B. Dutta, M. DeBellis arXiv ID 2009.01210 Category cs.IR: Information Retrieval Cross-listed cs.AI Citations 66 Venue International Conference on Knowledge Engineering and Ontology Development Last Checked 3 months ago
Abstract
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.
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