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"affiliations": [ { "name": "Computational Systems Biology Laboratory, University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil" } ], "person_or_org": { "family_name": "Tiago Lubiana", "identifiers": [ { "identifier": "0000-0003-2473-2313", "scheme": "orcid" } ], "name": "Tiago Lubiana", "type": "personal" } }, { "affiliations": [ { "name": "Institute of Child Health (ICH), Kolkata, India" } ], "person_or_org": { "family_name": "Diptanshu Das", "identifiers": [ { "identifier": "0000-0002-7221-5022", "scheme": "orcid" } ], "name": "Diptanshu Das", "type": "personal" } }, { "affiliations": [ { "name": "School of Data Science, University of Virginia, Charlottesville, Virginia, United States of America" } ], "person_or_org": { "family_name": "Daniel Mietchen", "identifiers": [ { "identifier": "0000-0001-9488-1870", "scheme": "orcid" } ], "name": "Daniel Mietchen", "type": "personal" } } ], "description": "
Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides a forum for exchanging structured data. In this research paper, we catalog the rules describing relational and statistical COVID-19 epidemiological data and implement them in SPARQL, a query language for semantic databases. We demonstrate the efficiency of our methods to evaluate structured information, particularly COVID-19 knowledge in Wikidata, and consequently in collaborative ontologies and knowledge graphs, and we show the advantages and drawbacks of our proposed approach by comparing it to other methods for validation of linked web data.
\n\nThis paper is a preprint and has not yet received peer-review.
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\r\n\r\nThe recent Corona Virus Disease (COVID-19) outbreak is requiring unseen efforts of collaboration of the scientific community that need to act fast and to share results in an unpredictable manner. In order to facilitate the Scientist efforts, this community was created to collect all research results that could be relevant for the scientific community working on the Corona Virus Disease (COVID-19) and SARS-CoV-2.
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