Using logical constraints to validate information in collaborative knowledge graphs: a study of COVID-19 on Wikidata

Tracking #: 2677-3891

This paper is currently under review
Authors: 
Houcemeddine Turki
Dariusz Jemielniak
Mohamed Ali Hadj Taieb
Jose Emilio Labra Gayo
Mohamed Ben Aouicha
Mus'ab Banat
Thomas Shafee
Eric Prud'hommeaux
Tiago Lubiana
Diptanshu Das
Daniel Mietchen

Responsible editor: 
Aidan Hogan

Submission type: 
Full Paper
Abstract: 
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.
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Under Review