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

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.