CORD-19: The COVID-19 Open Research Dataset
Abstract
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.
Cite
@article{arxiv.2004.10706,
title = {CORD-19: The COVID-19 Open Research Dataset},
author = {Lucy Lu Wang and Kyle Lo and Yoganand Chandrasekhar and Russell Reas and Jiangjiang Yang and Doug Burdick and Darrin Eide and Kathryn Funk and Yannis Katsis and Rodney Kinney and Yunyao Li and Ziyang Liu and William Merrill and Paul Mooney and Dewey Murdick and Devvret Rishi and Jerry Sheehan and Zhihong Shen and Brandon Stilson and Alex Wade and Kuansan Wang and Nancy Xin Ru Wang and Chris Wilhelm and Boya Xie and Douglas Raymond and Daniel S. Weld and Oren Etzioni and Sebastian Kohlmeier},
journal= {arXiv preprint arXiv:2004.10706},
year = {2020}
}
Comments
ACL NLP-COVID Workshop 2020