Representing COVID-19 information in collaborative knowledge graphs: The case of Wikidata

Semantic web

article

Houcemeddine Turki¹  Mohamed Ali Hadj Taieb²  Thomas Shafee³  Tiago Lubiana⁴  Dariusz Jemielniak⁵  Mohamed Ben Aouicha²  Jose Emilio Labra Gayo⁶  Eric A. Youngstrom⁷  Mus’ab Banat⁸  Diptanshu Das⁹  Daniel Mietchen^1,11 

[1] Faculty of Medicine of Sfax, University of Sfax;Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax;La Trobe University;Computational Systems Biology Laboratory, University of São Paulo;Department of Management in Networked and Digital Societies, Kozminski University;Web Semantics Oviedo ,(WESO) Research Group, University of Oviedo;Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill;Faculty of Medicine, Hashemite University;Institute of Child Health;Medical Superspecialty Hospital;School of Data Science, University of Virginia;Biomedical Data & Bioethics, Fraunhofer Institute for Biomedical Engineering

关键词: Public health surveillance;    Wikidata;    knowledge graph;    COVID-19;    SPARQL;    community curation;    FAIR data;    linked open data;   

DOI  :  10.3233/SW-210444

来源: IOS Press

【 摘 要 】

Information related to the COVID-19 pandemic ranges from biological to bibliographic, from geographical to genetic and beyond. The structure of the raw data is highly complex, so converting it to meaningful insight requires data curation, integration, extraction and visualization, the global crowdsourcing of which provides both additional challenges and opportunities. Wikidata is an interdisciplinary, multilingual, open collaborative knowledge base of more than 90 million entities connected by well over a billion relationships. It acts as a web-scale platform for broader computer-supported cooperative work and linked open data, since it can be written to and queried in multiple ways in near real time by specialists, automated tools and the public. The main query language, SPARQL, is a semantic language used to retrieve and process information from databases saved in Resource Description Framework (RDF) format.Here, we introduce four aspects of Wikidata that enable it to serve as a knowledge base for general information on the COVID-19 pandemic: its flexible data model, its multilingual features, its alignment to multiple external databases, and its multidisciplinary organization. The rich knowledge graph created for COVID-19 in Wikidata can be visualized, explored, and analyzed for purposes like decision support as well as educational and scholarly research.

【 授权许可】

Unknown