Open reproducible scientometric research with Alexandria3k

被引:3
|
作者
Spinellis, Diomidis [1 ,2 ]
机构
[1] Athens Univ Econ & Business, Dept Management Sci & Technol, Athens, Greece
[2] Delft Univ Technol, Dept Software Technol, Delft, Netherlands
来源
PLOS ONE | 2023年 / 18卷 / 11期
关键词
GOOGLE SCHOLAR; JOURNAL IMPACT; SCIENCE; COVID-19; REVIEWS; INDEX; TOOL;
D O I
10.1371/journal.pone.0294946
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:23
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