A Scientometric Analysis of Data Science Research in India (2014-2024) - Barman, Bikramaditya (Journal of Data Science, Informetrics, and Citation Studies, 2026)
The current study gives a scientometric analysis of data science research in India for a period of 10 years (2014-2024), and reflects the trends in its growth, the leading contributors and the impact of citation on it. In this analysis, we see high growth in research output across scientific domains, with data science for India dominated by the fields of Engineering, Chemical Sciences and Biological Sciences. Strong increase in research production on applied STEM fields, especially around AI and machine learning. This citation analysis indicates the significance of the Indian research organizations like the Department of Science and Technology (DST) and the Council of Scientific and Industrial Research (CSIR) which contribute significantly towards funding and the development of data science research in India. RSC Advances and PLOS ONE were identified as top journals for high-impact publications. The study further details that government agencies such as DST, UGC, and DBT are now entering as key players in supporting research funding. The results highlight India as an increasingly attractive hub for global data science research deliberations, building on an interdisciplinary tradition, increased government funding, and international collaboration.
Keywords: Data Science; Dimensions.AI Database; India; Research Trends; Scientometric Analysis