Research Article: “Daily Growth Rate of Scientific Production on Covid-19. Analysis in Databases and Open Access Repositories”
The following preprint was recently shared on arXiv. The complete article is in Spanish and was originally published here. An abstract/visualizations are available in English.
Title
Growth Rate of Scientific Production on Covid-19. Analysis in Databases and Open Access Repositories
Authors
Daniel Torres-Salinas
Universidad de Granada
Source
via arXiv
From the Abstract:
The scientific community is facing one of its greatest challenges in solving a global health problem: COVID-19 pandemic. This situation has generated an unprecedented volume of publications. What is the volume, in terms of publications, of research on COVID-19? The general objective of this research work is to obtain a global vision of the daily growth of scientific production on COVID-19 in different databases (Dimensions, Web of Science Core Collection, Scopus-Elsevier, Pubmed and eight repositories). In relation to the results obtained, Dimensions indexes a total of 9435 publications (69% with peer review and 2677 preprints) well above Scopus (1568) and WoS (718). This is a classic biliometric phenomenon of exponential growth (R2 = 0.92). The global growth rate is 500 publications and the production doubles every 15 days.
Direct Complete Abstract, Link to Full Text Article, and Data Visualizations
Filed under: Data Files, Elsevier, News, Open Access
About Gary Price
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.
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