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dc.contributor.authorQueralt-Rosinach, Núria
dc.contributor.authorSchofield, Paul N.
dc.contributor.authorHoehndorf, Robert
dc.contributor.authorWeiland, Claus
dc.contributor.authorSchultes, Erik Anthony
dc.contributor.authorBernabé, César Henrique
dc.contributor.authorRoos, Marco
dc.date.accessioned2021-08-16T11:51:18Z
dc.date.available2021-08-16T11:51:18Z
dc.date.issued2021-08-11
dc.identifier.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
dc.identifier.doi10.37044/osf.io/n6tcz
dc.identifier.urihttp://hdl.handle.net/10754/670637
dc.description.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.
dc.description.sponsorshipWe 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).
dc.publisherCenter for Open Science
dc.relation.urlhttps://osf.io/n6tcz
dc.rightsArchived with thanks to Center for Open Science. Authors retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC-BY).
dc.rights.urihttps://creativecommons.org/publicdomain/zero/1.0/legalcode
dc.titleThe COVID-19 epidemiology and monitoring ontology
dc.typePreprint
dc.contributor.departmentBio-Ontology Research Group (BORG)
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.eprint.versionPre-print
dc.contributor.institutionLeiden University Medical Center, The Netherlands
dc.contributor.institutionUniversity of Cambridge. United Kingdom
dc.contributor.institutionSenckenberg Biodiversity and Climate Research Center, Germany
dc.contributor.institutionGO FAIR Foundation
kaust.personHoehndorf, Robert
dc.relation.issupplementedbygithub:NuriaQueralt/covid19-epidemiology-ontology
refterms.dateFOA2021-08-16T11:53:09Z
display.relations<b>Is Supplemented By:</b><br/> <ul><li><i>[Software]</i> <br/> Title: NuriaQueralt/covid19-epidemiology-ontology: Epidemiology and monitoring ontology for COVID-19. Publication Date: 2020-11-09. github: <a href="https://github.com/NuriaQueralt/covid19-epidemiology-ontology" >NuriaQueralt/covid19-epidemiology-ontology</a> Handle: <a href="http://hdl.handle.net/10754/670689" >10754/670689</a></a></li></ul>


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Archived with thanks to Center for Open Science. Authors retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC-BY).
Except where otherwise noted, this item's license is described as Archived with thanks to Center for Open Science. Authors retain copyright and release the work under a Creative Commons Attribution 4.0 International License (CC-BY).