COVID-19 Literature Knowledge Graph

A large citation network of COVID-19 papers

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COVID-19 Meta-analysis Through a Literature Knowledge Graph

The Internet and Data Science Lab (IDLab-imec) created a Knowledge Graph from the recently published Kaggle dataset about COVID-19 literature (commonly known as CORD-19).

This Knownledge Graph contains different information for each paper such as author information, content information and citation information.

Additional information from external resources (such as DBpedia, Crossref, ORCID and BioPortal) were linked within this graph.

The creation process of this knowledge graph is open-sourced such that other research groups can extend, incorporate or link their knowledge within this graph.

Several version of this Graph are hosted on Kaggle, which eases the creation of useful applications. A starter notebook on how this knowledge graph can be used with Python can be found here:

Paper accepted at ISWC!

Our paper "Facilitating COVID-19 Meta-analysis Through a Literature Knowledge Graph" has been accepted to the resource track of the International Semantic Web Conference!

In case you use the COVID-KG in your research, please cite: "Steenwinckel B., Vandewiele G., Rausch I., Heyvaert P., Taelman R., Colpaert P., Simoens P., Dimou A., De Turck F. and Ongenae F. Facilitating COVID-19 Meta-analysis Through a Literature Knowledge Graph. In Proc. of 19th International Semantic Web Conference (ISWC), 2-6 November 2020 (accepted)"