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
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引用次数: 0
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.
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