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

• DOI: 10.48550/arxiv.2004.10706
• Publication Date: 2020-01-01
• Authors: Wang, Lucy Lu; Lo, Kyle; Chandrasekhar, Yo...; Reas, Russell; Yang, Jiangjiang; Burdick, Doug; Eide, Darrin; Funk, Kathryn; Katsis, Yannis; Kinney, Rodney; Li, Yunyao; Liu, Ziyang; Merrill, William; Mooney, Paul; Murdick, Dewey; Rishi, Devvret; Sheehan, Jerry; Shen, Zhihong; Stilson, Brandon; Wade, Alex; Wang, Kuansan; Wang, Nancy Xin Ru; Wilhelm, Chris; Xie, Boya; Raymond, Douglas; Weld, Daniel S.; Etzioni, Oren; Kohlmeier, Sebastian
• Keywords: FOS: Computer and information sciences; Computer Science - Computation and Language; 0202 electrical engineering, electronic engineering, information engineering; Computer Science - Digital Libraries; Digital Libraries (cs.DL); 02 engineering and technology; Computation and Language (cs.CL); 3. Good health

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.<br/>ACL NLP-COVID Workshop 2020<br/>