Enhancing Information Management: Automated Seamless Data Integration from Ethesis System to Library Management System of Kasetsart University Library

Abstract

Enhancing Information Management by automating data integration between Ethesis and Integrated Library System of Kasetsart University Library aimed to develop a system that automatically synchronizes data between Ethesis and Integrated Library System. This would enhance the efficiency of information resource management. Data integration of Ethesis with Integrated Library System involved study, analysis, design, and development of the system using Python3 programming language to automatically integrate the data. Testing the program with data 1,905 records from the DSpace repository from 2020 to 2023 revealed accurate integration results and a batch recording process could be used instead of individual entries to reduce the number of entries in the data. System development problems were observed in recording data in MARC21 format. DSpace repository data were not always accurate and complete. This led to errors in the data transformation process. In addition, once the data had been automatically recorded into Integrated Library System, they were immediately published in the WebOPAC without undergoing verification from staff. There should be an automatic addition of a "Suppressed" status to the data that have been recorded into Integrated Library System. This will enable staff to review the data before it is available to public. Furthermore, Ethesis was developed using DSpace version 5.4. Upgrading the version is recommended since there have been advancements in development up to version 7.6.