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Open reproducible scientometric research with Alexandria3k

Considerable scientific work involves locating, analyzing, systematizing, and synthesizing other publications, often with the help of online scientific publication databases and search engines. However, use of online sources suffers from a lack of repeatability and transparency, as well as from tech...

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Detalles Bibliográficos
Autor principal: Spinellis, Diomidis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688655/
https://www.ncbi.nlm.nih.gov/pubmed/38032908
http://dx.doi.org/10.1371/journal.pone.0294946
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author Spinellis, Diomidis
author_facet Spinellis, Diomidis
author_sort Spinellis, Diomidis
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description Considerable scientific work involves locating, analyzing, systematizing, and synthesizing other publications, often with the help of online scientific publication databases and search engines. However, use of online sources suffers from a lack of repeatability and transparency, as well as from technical restrictions. Alexandria3k is a Python software package and an associated command-line tool that can populate embedded relational databases with slices from the complete set of several open publication metadata sets. These can then be employed for reproducible processing and analysis through versatile and performant queries. We demonstrate the software’s utility by visualizing the evolution of publications in diverse scientific fields and relationships among them, by outlining scientometric facts associated with COVID-19 research, and by replicating commonly-used bibliometric measures and findings regarding scientific productivity, impact, and disruption.
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spelling pubmed-106886552023-12-01 Open reproducible scientometric research with Alexandria3k Spinellis, Diomidis PLoS One Research Article Considerable scientific work involves locating, analyzing, systematizing, and synthesizing other publications, often with the help of online scientific publication databases and search engines. However, use of online sources suffers from a lack of repeatability and transparency, as well as from technical restrictions. Alexandria3k is a Python software package and an associated command-line tool that can populate embedded relational databases with slices from the complete set of several open publication metadata sets. These can then be employed for reproducible processing and analysis through versatile and performant queries. We demonstrate the software’s utility by visualizing the evolution of publications in diverse scientific fields and relationships among them, by outlining scientometric facts associated with COVID-19 research, and by replicating commonly-used bibliometric measures and findings regarding scientific productivity, impact, and disruption. Public Library of Science 2023-11-30 /pmc/articles/PMC10688655/ /pubmed/38032908 http://dx.doi.org/10.1371/journal.pone.0294946 Text en © 2023 Diomidis Spinellis https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Spinellis, Diomidis
Open reproducible scientometric research with Alexandria3k
title Open reproducible scientometric research with Alexandria3k
title_full Open reproducible scientometric research with Alexandria3k
title_fullStr Open reproducible scientometric research with Alexandria3k
title_full_unstemmed Open reproducible scientometric research with Alexandria3k
title_short Open reproducible scientometric research with Alexandria3k
title_sort open reproducible scientometric research with alexandria3k
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688655/
https://www.ncbi.nlm.nih.gov/pubmed/38032908
http://dx.doi.org/10.1371/journal.pone.0294946
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