Gender differences, data carpentry and bibliometric studies in Mathematics

Abstract

Libraries deal with large amounts of data in the digital environment. Librarians manipulate, update and integrate data on e-journals & e-books every year to the new knowledge base or in their intended library software. Data need to be cleaned, transformed and refined before uploading. OpenRefine is a useful data wrangling tool to filter, clean and transform the data before migration. The paper exercises largescale data cleaning, extraction and analysis of publication data (81,729) downloaded from Scopus during 2016-2020 in the field of Mathematics where at least one author is affiliated with an Indian institute or University. The result shows that 76,712(93.86%) documents have DOIs; sharp increase in ORCID from 4.27% (2016) to 26.25% (2020). The paper also shed a light on gender analysis and the gravity of its disparity in the field of Mathematics. Based on first author analysis, the result reveals that 73% are male authors whereas 27% are female based on the study of over half-lakh papers on Mathematics, where at least one author is from India. There is extreme inequality in gender distribution in the scientific research publications in mathematics.

Keywords:

• Publication analysis
• Gender studies
• Mathematics
• OpenRefine
• JSON data extraction
• GREL
• Unpaywall
• Authorship trends