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COVID-19 Open Research Dataset
The COVID-19 Open Research Dataset is an extensive machine-readable resource of over 45,000 scholarly articles, including over 33,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community. This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease.
The dataset is updated weekly and contains all COVID-19 and coronavirus-related research (e.g., SARS, MERS) from the following sources: PubMed's PMC open access corpus (using this query: COVID-19 and coronavirus research), additional COVID-19 research articles from a corpus maintained by the World Health Organization (WHO), and bioRxiv and medRxiv pre-prints (using this query: COVID-19 and coronavirus research). Also available is a comprehensive metadata file of 44,000 coronavirus and COVID-19 research articles with links to PubMed, Microsoft Academic, and the WHO COVID-19 database of publications (includes articles without open access full text).