2020•The Korean Association of Urban PoliciesRequires access

Analysis on Integration Priority of City Service Data for Evolution of Existing City to Smart City

Joon Hyok Jo

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Abstract

The purpose of this study is to derive city service data that can improve the efficiency of urban management when integrated management and analysis among existing city service data of large cities and to analyze their integration priorities. Through this, we sought ways to evolve existing cities into data-driven smart cities. The case of this study is Goyang city where more than 1 million citizens live. The research methods are case analysis and in-depth interviews. The contents and types of 118 kinds of information systems and city services operated by Goyang City were analyzed, and two-level in-depth interviews were conducted for 36 department officials who operate them. Based on this, the priority of urban service data integration was derived by analyzing the degree of ease and demand for city service data integration. As a result, the high level of priority for integration among city service data was education, crime prevention, living environment, disaster prevention, and public transportation management. Therefore, it is better to consider the integration of city service data by prioritizing education, crime prevention, disaster prevention, living environment, and public transportation management when building infrastructure such as data hub center to build the foundation of data-driven smart cities.

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What this paper is about

The purpose of this study is to derive city service data that can improve the efficiency of urban management when integrated management and analysis among existing city service data of large cities and to analyze their integration priorities. Through this, we sought ways to evolve existing cities into data-driven smart cities. The case of this study is Goyang city where more than 1 million citizens live. The research methods are case analysis and in-depth interviews. The contents and types of 118 kinds of information systems and city services operated by Goyang City were analyzed, and two-level in-depth interviews were conducted for 36 department officials who operate them. Based on this, the priority of urban service data integration was derived by analyzing the degree of ease and demand for city service data integration. As a result, the high level of priority for integration among city service data was education, crime prevention, living environment, disaster prevention, and public transportation management. Therefore, it is better to consider the integration of city service data by prioritizing education, crime prevention, disaster prevention, living environment, and public transportation management when building infrastructure such as data hub center to build the foundation of data-driven smart cities.

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Available abstract

The purpose of this study is to derive city service data that can improve the efficiency of urban management when integrated management and analysis among existing city service data of large cities and to analyze their integration priorities. Through this, we sought ways to evolve existing cities into data-driven smart cities. The case of this study is Goyang city where more than 1 million citizens live. The research methods are case analysis and in-depth interviews. The contents and types of 118 kinds of information systems and city services operated by Goyang City were analyzed, and two-level in-depth interviews were conducted for 36 department officials who operate them. Based on this, the priority of urban service data integration was derived by analyzing the degree of ease and demand for city service data integration. As a result, the high level of priority for integration among city service data was education, crime prevention, living environment, disaster prevention, and public transportation management. Therefore, it is better to consider the integration of city service data by prioritizing education, crime prevention, disaster prevention, living environment, and public transportation management when building infrastructure such as data hub center to build the foundation of data-driven smart cities.

Key concepts: Smart city, Service (business), Emergency management, Public service, Business, Data integration, Computer security, Computer science

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