기본연구과제

This study aims to present strategies to establish a data-driven public administration based on results of analyzing the current status and actual conditions related to the implementation of data policies of local governments. Until now, there has been a lack of research on local governments, which are actually key stakeholders that generate, collect, and manage data. Due to the implementation of policies that failed to consider local governments in South Korea, the capabilities of local governments are actually falling short of the efforts and willingness to promote data-driven public administration at the central government level.
   Data-driven public administration is a comprehensive concept that encompasses data standardization and quality control, sharing and opening, and process improvement at the local government level, as well as decision-making using data. In addition, data-driven public administration includes the overall process related to data such as data collection, storage, processing, analysis, expression, and utilization. Through the review of cases and previous literature, we confirmed that data-driven public administration was discussed together with the concept of data sharing and opening, and public data and big data were also discussed as core concepts for data-driven public administration. Data-driven public administration is distinct from existing data-related policies in that it emphasizes the practical use of big data and public data.
   Through theoretical discussions, literature and case reviews, this study derived essential factors related to data-driven public administration at the local government level, such as securing institutional foundations, establishing and utilizing data-related processes, establishing cooperative systems, and preparing policies. The above-described factors were used to derive detailed analysis criteria constituting each analysis frame when analyzing the current status and case of this study. The institutional basis includes systems, organizations and human resources, and legal basis, and the process refers to management plans for data collection and production, sharing and provision, utilization and analysis, evaluation, and feedback. The use of data refers to the degree of use of public data and its level of improvement, the cooperation system refers to governance with various stakeholders such as central government ministries, local governments, public institutions, and entities in the private sector, and cooperation systems between departments within each local government. The degree of preparation for data-driven public administration includes the understanding of the policy and the level of awareness of employees for policy promotion.
   The analysis results for each criterion are as follows. Considering institutional basis, in terms of organizations, most local governments, existing data-related departments perform tasks for data-driven public administration. Depending on the size of the lower-level local governments, the department or team-level organization is in charge of the task. In addition, while many local governments operate several types of departments related to previous data policies, the criteria for classification between the relevant departments are ambiguous. In terms of human resources, most of the members who perform existing data-related tasks perform additional data-based administrative tasks. In terms of the budget, there was a difference in budget size between local governments, and it was confirmed that some local governments does not have their own budgets related to data-driven public administration. In terms of data-related systems, there are many system operations focused on data collection and management, while systems related to applications and in-depth stages such as analysis and utilization are insufficient. In terms of the legal basis, the frequency of securing data-driven public administration-related ordinances was relatively low compared to big data and public data-related ordinances. In terms of collaboration, local governments have data-related exchanges with various public and private sector stakeholders, and the former case is relatively more. In addition, we confirm that most of the data was used at the basic stage before policy making, such as policy reference and problem identification. Local governments have various types of unstructured data such as documents, images, videos, audio, and spatial information. The types of unstructured data in lower-level local governments are more diverse, and their frequency is measured higher than in upper-level local governments. The level of employees’ understanding and awareness of data-driven public administration was not high, and many competition-oriented projects are exist to spread public data and big data-related education programs and data-driven public administrative culture.
   In addition, this study found specific issues through in-depth interviews conducted for case analysis. These include contents such as awareness of data quality management, enactment of ordinances by local governments related to data-driven public administration, purchase of private data among collaborators, improvement of data-related systems, treatment of unstructured data.
   This study presented policy strategies that comprehensively considered the contents of the analysis criteria through the above-described analysis results and in-depth interviews. From an institutional perspective, the development and application of standard ordinances to enhance the effectiveness of policy promotion, the establishment and status of a data-driven public administrative organizational system, and the improvement of guidelines necessary for data utilization and sharing were presented. In terms of operation, we suggested to establish an official form of collaboration system for cooperation, revitalize a platform for efficient data management and sharing, continuously cultivate and deploy appropriate human resources, and secure budgets for policy promotion. In terms of evaluation and post management, the development and application of evaluation indicators to strengthen related education necessary for promoting and raising awareness of data-driven public administration were considered. Finally, this study classified the main entities of data-driven public administration into central government ministries and local governments, and presented the roles of each entities.