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COVID-19: A scholarly production dataset report for research analysis

COVID-2019 has been recognized as a global threat, and several studies are being conducted in order to contribute to the fight and prevention of this pandemic. This work presents a scholarly production dataset focused on COVID-19, providing an overview of scientific research activities, making it po...

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Autores principales: Santos, Breno Santana, Silva, Ivanovitch, Ribeiro-Dantas, Marcel da Câmara, Alves, Gisliany, Endo, Patricia Takako, Lima, Luciana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7434621/
https://www.ncbi.nlm.nih.gov/pubmed/32837978
http://dx.doi.org/10.1016/j.dib.2020.106178
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author Santos, Breno Santana
Silva, Ivanovitch
Ribeiro-Dantas, Marcel da Câmara
Alves, Gisliany
Endo, Patricia Takako
Lima, Luciana
author_facet Santos, Breno Santana
Silva, Ivanovitch
Ribeiro-Dantas, Marcel da Câmara
Alves, Gisliany
Endo, Patricia Takako
Lima, Luciana
author_sort Santos, Breno Santana
collection PubMed
description COVID-2019 has been recognized as a global threat, and several studies are being conducted in order to contribute to the fight and prevention of this pandemic. This work presents a scholarly production dataset focused on COVID-19, providing an overview of scientific research activities, making it possible to identify countries, scientists and research groups most active in this task force to combat the coronavirus disease. The dataset is composed of 40,212 records of articles’ metadata collected from Scopus, PubMed, arXiv and bioRxiv databases from January 2019 to July 2020. Those data were extracted by using the techniques of Python Web Scraping and preprocessed with Pandas Data Wrangling. In addition, the pipeline to preprocess and generate the dataset are versioned with the Data Version Control tool (DVC) and are thus easily reproducible and auditable.
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spelling pubmed-74346212020-08-19 COVID-19: A scholarly production dataset report for research analysis Santos, Breno Santana Silva, Ivanovitch Ribeiro-Dantas, Marcel da Câmara Alves, Gisliany Endo, Patricia Takako Lima, Luciana Data Brief Social Science COVID-2019 has been recognized as a global threat, and several studies are being conducted in order to contribute to the fight and prevention of this pandemic. This work presents a scholarly production dataset focused on COVID-19, providing an overview of scientific research activities, making it possible to identify countries, scientists and research groups most active in this task force to combat the coronavirus disease. The dataset is composed of 40,212 records of articles’ metadata collected from Scopus, PubMed, arXiv and bioRxiv databases from January 2019 to July 2020. Those data were extracted by using the techniques of Python Web Scraping and preprocessed with Pandas Data Wrangling. In addition, the pipeline to preprocess and generate the dataset are versioned with the Data Version Control tool (DVC) and are thus easily reproducible and auditable. Elsevier 2020-08-19 /pmc/articles/PMC7434621/ /pubmed/32837978 http://dx.doi.org/10.1016/j.dib.2020.106178 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Social Science
Santos, Breno Santana
Silva, Ivanovitch
Ribeiro-Dantas, Marcel da Câmara
Alves, Gisliany
Endo, Patricia Takako
Lima, Luciana
COVID-19: A scholarly production dataset report for research analysis
title COVID-19: A scholarly production dataset report for research analysis
title_full COVID-19: A scholarly production dataset report for research analysis
title_fullStr COVID-19: A scholarly production dataset report for research analysis
title_full_unstemmed COVID-19: A scholarly production dataset report for research analysis
title_short COVID-19: A scholarly production dataset report for research analysis
title_sort covid-19: a scholarly production dataset report for research analysis
topic Social Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7434621/
https://www.ncbi.nlm.nih.gov/pubmed/32837978
http://dx.doi.org/10.1016/j.dib.2020.106178
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