Open AccessCovid-19 knowledge graphs in Health Communication and Information
Author(s) -
Andrew Iliadis
Publication year - 2021
Publication title -
reciis
Language(s) - English
Resource type - Journals
eISSN - 1981-6286
pISSN - 1981-6278
DOI - 10.29397/reciis.v15i1.2239
Subject(s) - knowledge graph , popularity , covid-19 , metadata , salient , computer science , pandemic , knowledge management , data science , semantics (computer science) , world wide web , political science , information retrieval , artificial intelligence , medicine , disease , pathology , infectious disease (medical specialty) , law , programming language
This commentary discusses recent developments in ‘knowledge graph’ technology over the course of the Covid-19 pandemic. Recently experiencing a surge in popularity, knowledge graphs are technologies that assist with data integration through structured metadata modeling. Researchers tag and collate vast amounts of diverse data using knowledge graphs, yet problems related to semantic drift and more salient issues related to the political economy of information and communication technologies persist. Researchers should anticipate that the semantics of these Covid-19 knowledge graphs can change over time. Equally important, researchers should also consider all stakeholders involved, including those stakeholders that might be excluded.