Exploring the Research Impact of Works on Vedic Mathematics using Data Carpentry: A Multi-Metric Analysis

Authors

  • Department of Library and Information Science, University of Kalyani, Kalyani, Nadia – 741201, West Bengal

DOI:

https://doi.org/10.17821/srels/2025/v62i4/171738

Keywords:

Altmetric Analysis, Citation Analysis, Data Carpentry, Mathematics, OpenAlex, OpenRefine, Research Impact, Smart Citations, Vedic Mathematics

Abstract

Vedic mathematics is a rich heritage that Indians have inherited. It allows an easy approach to working with numbers and solving numerical problems. With the increasing need for mathematical aptitude in all domains of society, we need to develop sharp calculation skills, making the need for Vedic mathematics justified. While much research has been done on this topic, the question is how impactful the research has been. Multiple metrics measure the impact of scholarly research. This research aims to explore various ways of measuring the impact of published research on Vedic mathematics, including an analysis of multiple types of citations and altmetric analysis. This research aims to predict the amount of awareness of this topic among scholarly people and others in general. This research uses a data carpentry-based approach on the bibliographic data fetched from OpenAlex. using OpenRefine, a data wrangling tool, and API services of different providers of citation and altmetric data. The result of the research showed that the different services used, namely OpenCitations Corpus, Dimensions.ai, and Scite.ai, each provided different citation counts, since all of them had different amounts of coverage of citation data. But as compared to the data provided by the mentioned services, Altmetric.com provided very less coverage of altmetric data. We conclude that the topic of Vedic mathematics still requires much more attention from society.

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Published

2025-08-01

How to Cite

Dasgupta, T. (2025). Exploring the Research Impact of Works on Vedic Mathematics using Data Carpentry: A Multi-Metric Analysis. Journal of Information and Knowledge, 62(4), 269–274. https://doi.org/10.17821/srels/2025/v62i4/171738

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