A community effort for COVID-19 Ontology Harmonization

Asiyah Yu Lin; Yuki Yamagata; William D Duncan; Leigh C Carmody; Tatsuya Kushida; Hiroshi Masuya; John Beverley; Biswanath Dutta; Michael DeBellis; Zoë May Pendlington; Paola Roncaglia; Yongqun He

A community effort for COVID-19 Ontology Harmonization

CEUR Workshop Proc. 2022:3073:122-127. Epub 2022 Jan 28.

Authors

Affiliations

¹ National Human Genome Research Institute, NIH, Bethesda, MD, USA.
² RIKEN, Japan.
³ Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
⁴ The Jackson Laboratory, Bar Harbor, ME, USA.
⁵ Northwest University, Evanston, Il, USA.
⁶ Indian Statistical Institute Bangalore Centre, India.
⁷ Individual Consultant and Researcher, San Francisco, CA, USA.
⁸ European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
⁹ University of Michigan Medical School, Ann Arbor, MI, USA.

PMID: 37324543
PMCID: PMC10262777

Abstract

Ontologies have emerged to become critical to support data and knowledge representation, standardization, integration, and analysis. The SARS-CoV-2 pandemic led to the rapid proliferation of COVID-19 data, as well as the development of many COVID-19 ontologies. In the interest of supporting data interoperability, we initiated a community-based effort to harmonize COVID-19 ontologies. Our effort involves the collaborative discussion among developers of seven COVID-19 related ontologies, and the merging of four ontologies. This effort demonstrates the feasibility of harmonizing these ontologies in an interoperable framework to support integrative representation and analysis of COVID-19 related data and knowledge.

Keywords: COVID-19; Knowledge integration; SARS-CoV-2; harmonization; ontology.

Abstract

Grants and funding