TY - JOUR TI - Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata AU - Turki, Houcemeddine AU - Jemielniak, Dariusz AU - Hadj Taieb, Mohamed A. AU - Labra Gayo, Jose E. AU - Ben Aouicha, Mohamed AU - Banat, Mus’ab AU - Shafee, Thomas AU - Prud’hommeaux, Eric AU - Lubiana, Tiago AU - Das, Diptanshu AU - Mietchen, Daniel T2 - PeerJ Computer Science AB - Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides an ideal forum for exchanging structured data that can be verified and consolidated using validation schemas and bot edits. In this research article, we catalog an automatable task set necessary to assess and validate the portion of Wikidata relating to the COVID-19 epidemiology. These tasks assess statistical data and are implemented in SPARQL, a query language for semantic databases. We demonstrate the efficiency of our methods for evaluating structured non-relational information on COVID-19 in Wikidata, and its applicability in collaborative ontologies and knowledge graphs more broadly. We show the advantages and limitations of our proposed approach by comparing it to the features of other methods for the validation of linked web data as revealed by previous research. DA - 2022/09/29/ PY - 2022 DO - 10.7717/peerj-cs.1085 DP - DOI.org (Crossref) VL - 8 SP - e1085 LA - en SN - 2376-5992 ST - Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs UR - https://peerj.com/articles/cs-1085 Y2 - 2022/10/05/21:42:46 ER -