Published September 24, 2020 | Version v3

Wikidata and COVID-19: Creating a collaborative knowledge graph from CORD-19 scholarly publications

Authors/Creators

  • 1. University of Sfax, Tunisia

Description

Knowledge graphs are an essential ingredient for information systems to handle the ever growing COVID-19 data on a daily basis. This presentation explains how open and collaborative FAIR knowledge bases like Wikidata can be useful to create a large-scale semantic representation of COVID-19 information from CORD-19 scholarly publications. I give an overview of how a data model has been collaboratively developed and maintained for COVID-19 knowledge, and I provide a detailed snapshot about the various methods used to extract items and statements from CORD-19 research papers. Then, I outline the tools for the enrichment of COVID-19 information on Wikidata as well as the knowledge graph validation methods applicable to COVID-19 knowledge. Finally, I describe the COVID-19 information in Wikidata and discuss its usefulness in supporting human decisions and social recommendations about the infectious disease.

Files

AI2 (1).pdf

Files (23.9 MB)

Name Size Download all
md5:8d16e58941b379a715ec4f70604b0386
6.5 MB Preview Download
md5:a0de44892e8b2910233947ab7bd38741
17.5 MB Download