Journal of Information Science Theory and Practice

  • 제12권3호
  • /
  • Pages.49-62
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  • 2024
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  • 2287-9099(pISSN)
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  • 2287-4577(eISSN)
한국과학기술정보연구원 과학기술정보센터 (Korea Institute of Science and Technology Information)
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The MapDS-Onto Framework for Matching Formula Factors of KPIs and Database Schema: A Case Study of the Prince of Songkla University

  • Kittisak Kaewninprasert (Program in Data Science, College of Digital Science, Prince of Songkla University, Hat Yai Campus) ;
  • Supaporn Chai-Arayalert (Department of Information Technology, Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus) ;
  • Narueban Yamaqupta (Department of Tourism Management, Faculty of Commerce and Management, Prince of Songkla University, Trang Campus)
  • 투고 : 2023.04.18
  • 심사 : 2024.05.18
  • 발행 : 2024.09.30
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초록

Strategy monitoring is essential for business management and for administrators, including managers and executives, to build a data-driven organization. Having a tool that is able to visualize strategic data is significant for business intelligence. Unfortunately, there are gaps between business users and information technology departments or business intelligence experts that need to be filled to meet user requirements. For example, business users want to be self-reliant when using business intelligence systems, but they are too inexperienced to deal with the technical difficulties of the business intelligence systems. This research aims to create an automatic matching framework between the key performance indicators (KPI) formula and the data in database systems, based on ontology concepts, in the case study of Prince of Songkla University. The mapping data schema with ontology (MapDSOnto) framework is created through knowledge adaptation from the literature review and is evaluated using sample data from the case study. String similarity methods are compared to find the best fit for this framework. The research results reveal that the "fuzz.token_set_ratio" method is suitable for this study, with a 91.50 similarity score. The two main algorithms, database schema mapping and domain schema mapping, present the process of the MapDS-Onto framework using the "fuzz.token_set_ratio" method and database structure ontology to match the correct data of each factor in the KPI formula. The MapDS-Onto framework contributes to increasing self-reliance by reducing the amount of database knowledge that business users need to use semantic business intelligence.

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과제정보

This work was supported by the Digital Science for Economy, Society, Human Resources Innovative Development and Environment project, funded by Reinventing Universities & Research Institutes under grant no. 2046735, Ministry of Higher Education, Science, Research and Innovation, Thailand.

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