국내 공공데이터 플랫폼의 개방 성과 분석 및 평가모델 실증사례 연구
Open Performance Analysis of Domestic Government Data Platform and Case Study on the Evaluation Model
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초록
이 연구에서는 국내 공공데이터의 제공 및 이용 활성화를 위한 기본계획(제1차 2014~제4차 2025)에 나타난 공공데이터 플랫폼 추진 경과 및 공공데이터 개방 성과에 대해 설명한다. 아울러 현안으로 추진되고 있는 제4차 국가 중점데이터 개방계획 추진 이슈, 관리체계 개선 이슈, 이용 활성화 이슈 등을 토대로 공공데이터 개방현황을 분석한다. 끝으로 공공의 안전과 개인의 프라이버시 보장을 위해 중국 4개 지역의 빅데이터 기반 OGDP(Open Government Data Platform)를 통해 4가지 파일럿 영역<Data/Platform/Outcome/Citizen)에서 평가모델을 구축한 실증 연구사례를 제시한다. 공공기관의 데이터 플랫폼 구축을 통한 데이터 개방은 경제적 측면, 사회적 측면, 행정적인 측면에서 다양한 가치를 창출하고 있다. 향후에는 다양한 데이터 제공 이슈들을 정보이용자(기업, 민간 등 공공데이터 수요자)의 관점에서 고부가가치 서비스를 제공할 수 있는 선진 연구가 필요하다. 아울러 데이터 산업(사업)을 보다 효과적으로 활성화하기 위해서는 ⅰ)데이터 전문인력 양성에 필요한 정책적 지원, ⅱ)데이터 전문인력 매칭 서비스 지원 및 지속적인 재직자 데이터 직무능력 향상 교육 등이 필요하다. 이를 통해 데이터 기술 시장을 확대하여 글로벌 시장 선점을 위한 기반을 마련하는 데 주력할 필요가 있다.
Abstract
This study explains the progress of the public data platform promotion and the results of open government data shown in the basic plan of domestic public data(1st 2014~4th 2025). In addition, the current status of open government data is analyzed based on the issue of promoting the 4th National Key Data Open Plan, the issue of improving the management system, and the issue of activating its use, which are being promoted as pending issues. Finally, in order to ensure public safety and personal privacy, we present an empirical research case in which an evaluation model was built in four pilot areas<Data/Platform/Outcome/Citizen) through the big data-based OGDP(Open Government Data Platform) in four regions of China. Data openness through the establishment of data platforms by public institutions is creating various values in economic, social, and administrative aspects. In the future, advanced research is needed to provide high-value-added services from the perspective of information users(public data consumers such as companies and the private sector) on various data provision issues. In addition, in order to more effectively revitalize the data industry(business), it is necessary to i) provide policy support for fostering data experts, and ii) support for data expert matching services and continuous training to improve data skills for incumbents. Through this, it is necessary to focus on expanding the data technology market and laying the foundation for preemption in the global market.
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