KKU-BiblioMerge: A novel tool for multi-database integration in bibliometric analysis

Authors

DOI:

https://doi.org/10.47909/ijsmc.157

Keywords:

multi-database integration, bibliometric tool, scientometric analysis, data deduplication, cross-platform analysis, KKU-BiblioMerge

Abstract

Objective. The objective of this study was to develop and validate KKU-BiblioMerge V.1.0, a bibliometric tool designed to address the limitations of single-source data in bibliometric analysis by integrating data from multiple databases, specifically Scopus and Web of Science (WoS).

Design/Methodology/Approach. The tool was developed using the R Shiny framework and incorporated key functions for data deduplication, field mapping, and integrity checks to ensure effective dataset merging. The performance of KKU-BiblioMerge was assessed by testing its ability to import, merge, and export bibliometric data, focusing on the efficiency and accuracy of consolidating records from Scopus and WoS.

Findings. The KKU-BiblioMerge application effectively processed and integrated 686 initial documents, eliminating 24.49% duplicate records to produce a final dataset of 518 unique entries. The tool demonstrated strong data consistency and high accuracy in field mapping, offering reliable cross-platform integration of bibliometric data compared to tools such as VOSviewer and Biblioshiny.

Originality/Value. KKU-BiblioMerge V.1.0 was a user-friendly, robust solution for multi-database bibliometric analysis. It enabled a more comprehensive and unbiased understanding of research landscapes. Its capability to integrate diverse datasets laid a foundation for advancing bibliometric software, broadening the scope and accuracy of analyses across scientific domains.

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Published

2025-02-01

How to Cite

Chansanam, W., & Li, C. (2025). KKU-BiblioMerge: A novel tool for multi-database integration in bibliometric analysis. Iberoamerican Journal of Science Measurement and Communication, 5(1), 1–16. https://doi.org/10.47909/ijsmc.157