CORD-19: The Covid-19 Open Research Dataset.


Journal

ArXiv
ISSN: 2331-8422
Titre abrégé: ArXiv
Pays: United States
ID NLM: 101759493

Informations de publication

Date de publication:
22 Apr 2020
Historique:
pubmed: 9 6 2020
medline: 9 6 2020
entrez: 9 6 2020
Statut: epublish

Résumé

The Covid-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on Covid-19 and related historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information retrieval systems over its rich collection of metadata and structured full text papers. Since its release, CORD-19 has been downloaded over 200K times and has served as the basis of many Covid-19 text mining and discovery systems. In this article, we describe the mechanics of dataset construction, highlighting challenges and key design decisions, provide an overview of how CORD-19 has been used, and describe several shared tasks built around the dataset. We hope this resource will continue to bring together the computing community, biomedical experts, and policy makers in the search for effective treatments and management policies for Covid-19.

Identifiants

pubmed: 32510522
pii: 2004.10706
pmc: PMC7251955
pii:

Types de publication

Preprint

Langues

eng

Auteurs

Lucy Lu Wang (LL)

Allen Institute for AI.

Kyle Lo (K)

Allen Institute for AI.

Yoganand Chandrasekhar (Y)

Allen Institute for AI.

Russell Reas (R)

Allen Institute for AI.

Jiangjiang Yang (J)

Allen Institute for AI.

Douglas Burdick (D)

IBM Research.

Darrin Eide (D)

Microsoft Research.

Kathryn Funk (K)

National Library of Medicine.

Yannis Katsis (Y)

IBM Research.

Rodney Kinney (R)

Allen Institute for AI.

Yunyao Li (Y)

IBM Research.

Ziyang Liu (Z)

Chan Zuckerberg Initiative.

William Merrill (W)

Allen Institute for AI.

Dewey Murdick (D)

Georgetown University.

Jerry Sheehan (J)

National Library of Medicine.

Zhihong Shen (Z)

Microsoft Research.

Brandon Stilson (B)

Allen Institute for AI.

Alex D Wade (AD)

Chan Zuckerberg Initiative.

Kuansan Wang (K)

Microsoft Research.

Chris Wilhelm (C)

Allen Institute for AI.

Boya Xie (B)

Microsoft Research.

Douglas Raymond (D)

Allen Institute for AI.

Daniel S Weld (DS)

Allen Institute for AI.
University of Washington.

Oren Etzioni (O)

Allen Institute for AI.

Sebastian Kohlmeier (S)

Allen Institute for AI.

Classifications MeSH