Date of this Version

Summer 4-7-2026

Document Type

Article

Citation

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Abstract

Big Data can be defined as high-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for improved insight and decision-making. Library and Information Centres generate and manage vast amounts of data through digital catalogs, circulation systems, user queries, and digital repositories. The main purpose of the study is to analyze big data research in Library and Information Science in India from 2015 to 2024. It conducted a quantitative analysis using the Bibliometrix tool on scientific production indexed in the Scopus database. A total of 1639 documents were retrieved and exported in CSV format. MS Office 2013, the Biblioshiny Web Interface, and VOSviewer are used for data analysis and visualization. They will identify the annual scientific production with citation impact and most prolific contributors, including sources, authors, and organizations. It also identifies the most frequently occurring keywords, emerging research trend topics, and thematic structure related to big data research in LIS publications in India. Findings show that the journal Intelligent Systems Reference Library is recognized as the most productive source, while Kumar S appears as the most prolific author. The University of Kashmir has found the most prolific contributor with the highest number of publications. The most frequently occurring keywords in big data in LIS in India include ‘machine learning’, ‘artificial intelligence’, ‘deep learning’, ‘big data’, ‘bibliometric analysis’, ‘blockchain’, ‘sentiment analysis’, ‘scientometrics’, ‘bibliometrics’, and ‘social media.’ Furthermore, the thematic map defines the dynamic nature of the research theme, such as ‘scientometrics’, ‘bibliometrics’, and ‘India’, which emerge as central areas of investigation in research. The study is valuable for researchers, educators, Scientists, institutions, and individuals in the LIS field.

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