철도 산업의 공기 질 데이터베이스 연합형 통합을 위한 지능형 데이터 거버넌스
Intelligent Data Governance for the Federated Integration of Air Quality Databases in the Railway Industry
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Purpose: In this paper, we will discuss 1) prioritizing databases to be integrated; 2) which data elements should be emphasized in federated database integration; and 3) the degree of efficiency in the integration. This paper aims to lay the groundwork for building data governance by presenting guidelines for database integration using metrics to identify and evaluate the capabilities of the UK's air quality databases. Methods: This paper intends to perform relative efficiency analysis using Data Envelope Analysis among the multi-criteria decision-making methods. In federated database integration, it is important to identify databases with high integration efficiency when prioritizing databases to be integrated. Results: The outcome of this paper aims not to present performance indicators for the implementation and evaluation of data governance, but rather to discuss what criteria should be used when performing 'federated integration'. Using Data Envelope Analysis in the process of implementing intelligent data governance, authors will establish and present practical strategies to discover databases with high integration efficiency. Conclusion: Through this study, it was possible to establish internal guidelines from an integrated point of view of data governance. The flexiblity of the federated database integration under the practice of the data governance, makes it possible to integrate databases quickly, easily, and effectively. By utilizing the guidelines presented in this study, authors anticipate that the process of integrating multiple databases, including the air quality databases, will evolve into the intelligent data governance based on the federated database integration when establishing the data governance practice in the railway industry.
Abstract
Purpose: In this paper, we will discuss 1) prioritizing databases to be integrated; 2) which data elements should be emphasized in federated database integration; and 3) the degree of efficiency in the integration. This paper aims to lay the groundwork for building data governance by presenting guidelines for database integration using metrics to identify and evaluate the capabilities of the UK's air quality databases. Methods: This paper intends to perform relative efficiency analysis using Data Envelope Analysis among the multi-criteria decision-making methods. In federated database integration, it is important to identify databases with high integration efficiency when prioritizing databases to be integrated. Results: The outcome of this paper aims not to present performance indicators for the implementation and evaluation of data governance, but rather to discuss what criteria should be used when performing 'federated integration'. Using Data Envelope Analysis in the process of implementing intelligent data governance, authors will establish and present practical strategies to discover databases with high integration efficiency. Conclusion: Through this study, it was possible to establish internal guidelines from an integrated point of view of data governance. The flexiblity of the federated database integration under the practice of the data governance, makes it possible to integrate databases quickly, easily, and effectively. By utilizing the guidelines presented in this study, authors anticipate that the process of integrating multiple databases, including the air quality databases, will evolve into the intelligent data governance based on the federated database integration when establishing the data governance practice in the railway industry.
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