Schofield, Paul N.
Schultes, Erik Anthony
Bernabé, César Henrique
KAUST DepartmentBio-Ontology Research Group (BORG)
Computational Bioscience Research Center (CBRC)
Computer Science Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/670637
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AbstractThe novel COVID-19 infectious disease emerged and spread, causing high mortality and morbidity rates worldwide. In the OBO Foundry, there are more than one hundred ontologies to share and analyse large-scale datasets for biological and biomedical sciences. However, this pandemic revealed that we lack tools for an efficient and timely exchange of this epidemiological data which is necessary to assess the impact of disease outbreaks, the efficacy of mitigating interventions and to provide a rapid response. In this study we present our findings and contributions for the bio-ontologies community.
CitationQueralt-Rosinach, N., Schofield, P., Hoehndorf, R., Weiland, C., Schultes, E. A., Bernabé, C. H., & Roos, M. (2021). The COVID-19 epidemiology and monitoring ontology. doi:10.37044/osf.io/n6tcz
SponsorsWe would like to specially thank Birgit Meldal for her input and ideas. This initiative has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°825575 (the European Joint Programme Rare Diseases), and the Trusted World of Corona (TWOC; LSH Health Holland).
PublisherCenter for Open Science
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