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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2023
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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 |
Sumario: | 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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