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

Biswanath Dutta, Michael DeBellis

2020

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 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.

Paper Citation

in Harvard Style

Dutta B. and DeBellis M. (2020). CODO: An Ontology for Collection and Analysis of Covid-19 Data. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD; ISBN 978-989-758-474-9, SciTePress, pages 76-85. DOI: 10.5220/0010112500760085

in Bibtex Style

@conference{keod20,
author={Biswanath Dutta and Michael DeBellis},
title={CODO: An Ontology for Collection and Analysis of Covid-19 Data},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD},
year={2020},
pages={76-85},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010112500760085},
isbn={978-989-758-474-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD
TI - CODO: An Ontology for Collection and Analysis of Covid-19 Data
SN - 978-989-758-474-9
AU - Dutta B.
AU - DeBellis M.
PY - 2020
SP - 76
EP - 85
DO - 10.5220/0010112500760085
PB - SciTePress