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CORD-19: The Covid-19 Open Research Dataset
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 fu...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251955/ https://www.ncbi.nlm.nih.gov/pubmed/32510522 |
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author | Wang, Lucy Lu Lo, Kyle Chandrasekhar, Yoganand Reas, Russell Yang, Jiangjiang Burdick, Douglas 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 D. Wang, Kuansan Wang, Nancy Xin Ru Wilhelm, Chris Xie, Boya Raymond, Douglas Weld, Daniel S. Etzioni, Oren Kohlmeier, Sebastian |
author_facet | Wang, Lucy Lu Lo, Kyle Chandrasekhar, Yoganand Reas, Russell Yang, Jiangjiang Burdick, Douglas 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 D. Wang, Kuansan Wang, Nancy Xin Ru Wilhelm, Chris Xie, Boya Raymond, Douglas Weld, Daniel S. Etzioni, Oren Kohlmeier, Sebastian |
author_sort | Wang, Lucy Lu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7251955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cornell University |
record_format | MEDLINE/PubMed |
spelling | pubmed-72519552020-06-07 CORD-19: The Covid-19 Open Research Dataset Wang, Lucy Lu Lo, Kyle Chandrasekhar, Yoganand Reas, Russell Yang, Jiangjiang Burdick, Douglas 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 D. Wang, Kuansan Wang, Nancy Xin Ru Wilhelm, Chris Xie, Boya Raymond, Douglas Weld, Daniel S. Etzioni, Oren Kohlmeier, Sebastian ArXiv Article 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. Cornell University 2020-04-22 /pmc/articles/PMC7251955/ /pubmed/32510522 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Wang, Lucy Lu Lo, Kyle Chandrasekhar, Yoganand Reas, Russell Yang, Jiangjiang Burdick, Douglas 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 D. Wang, Kuansan Wang, Nancy Xin Ru Wilhelm, Chris Xie, Boya Raymond, Douglas Weld, Daniel S. Etzioni, Oren Kohlmeier, Sebastian CORD-19: The Covid-19 Open Research Dataset |
title | CORD-19: The Covid-19 Open Research Dataset |
title_full | CORD-19: The Covid-19 Open Research Dataset |
title_fullStr | CORD-19: The Covid-19 Open Research Dataset |
title_full_unstemmed | CORD-19: The Covid-19 Open Research Dataset |
title_short | CORD-19: The Covid-19 Open Research Dataset |
title_sort | cord-19: the covid-19 open research dataset |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251955/ https://www.ncbi.nlm.nih.gov/pubmed/32510522 |
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