• Journal of Korean Society of Archives and Records Management
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• v.21 no.4
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• pp.1-18
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• 2021

Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.

• Journal of the HCI Society of Korea
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• v.10 no.1
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• pp.5-17
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• 2015

Nowadays various public data have been serviced to the public. Through the opening of public data, the transparency and effectiveness of public policy developed by governments are increased and users can lead to the growth of industry related to public data. Since end-users of using public data are citizens, it is very important for everyone to figure out the meaning of public data using proper visualization techniques. In this work, to indicate the significance of widespread public data, we consider UN voting record as public data in which many people may be interested. In general, it has high utilization value by diplomatic and educational purposes, and is available in public. If we use proper data mining and visualization algorithms, we can get an insight regarding the voting patterns of UN members. To visualize, it is necessary to measure the voting similarity values among UN members and then a social graph is created by the similarity values. Next, using a graph layout algorithm, the social graph is rendered on the screen. If we use the existing method for visualizing the social graph, it is hard to understand the meaning of the social graph because the graph is usually dense. To improve the weak point of the existing social graph visualization, we propose Friend-Matching, Friend-Rival Matching, and Bubble Heap algorithms in this paper. We also validate that our proposed algorithms can improve the quality of visualizing social graphs displayed by the existing method. Finally, our prototype system has been released in http://datalab.kunsan.ac.kr/politiz/un/. Please, see if it is useful in the aspect of public data utilization.

• Information Systems Review
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• v.20 no.2
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• pp.1-19
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• 2018

In many countries, governments invest a substantial amount of budget in open government data (OGD) for governmental performance and transparency. To understand the actual performance of such policies, the governments should measure the realized value. Many organizations and researchers have attempted to assess the value of OGD. However, they have neglected a perspective of consumers who benefit from OGD. Moreover, little research has quantified the economic value. This research examines extant methods of intangible asset valuation to quantify the economic value of OGD in a citizen perspective. In consideration of the extant research methods and the characteristics of OGD, the contingent valuation method is the most appropriate because it effectively reflects various users and their purpose of use. We then conduct a survey of citizens living in Seoul, Korea and assess the economic value of OGD provided by the Seoul government. Findings show that citizens' willingness to pay (WTP) differs across respondents' prior experience, tax resistance, perceived benefit and perceived reality of virtual scenario, but it does not differ across their demographics. WTP also significantly varies across the question formats. We discuss the reliability of the results and implications for future research.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.95-96
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• 2021

본 논문에서는, 서울시 자치구별 공공데이터를 활용한 분석 정보를 통해, 도시가 어떤 구조와 산업으로 형성되었는지 알아본다. 데이터 분석을 통해 얻어진 서울의 특징과 도시(자치구별)의 교통 측면, 상업, 데이터에서 발견한 정보를 통해 도시 특성과 구조를 알아본다. 본 논문에서 연구한 결과는 스마트 도시 정책에 활용하여 도시 기본 설계시 교통, 주거, 상업 등의 효율성을 증대 시키는데 기본 자료로 활용할 수 있다.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.285-293
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• 2021

With the advent of the 4th Industrial Revolution, AI utilization capabilities are being emphasized in various industries, but AI education design and curriculum research as universal education is currently lacking. This study offers a design for universal AI education to further cultivate its use in universities. For the AI basic education design, a questionnaire was conducted for experts three times, and the reliability of the derived design contents was verified by reflecting the results. As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived were data structure understanding and processing, visualization, word cloud, public data utilization, and machine learning concept understanding and utilization. The educational design content derived through this study is expected to increase the value of competency-centered AI universal education in the future.

• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.119-122
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• 2013

정부 및 기관, 개인에게 부가가치를 제공하는 공공 오픈데이터를 Linked Data로 발행하기 위한 다양한 시도들이 계속되고 있는 현 상황에서, 공공 오픈데이터인 '서울역사박물관의 유물 데이터'를 대상으로 데이터 정제 및 Linked Data로 발행하는 작업을 수행하여 발행 과정에서 나타나는 제약사항들에 대해 검토하였다. 이를 통해 정부 및 각 기관들, 개인이 데이터 발행자 및 이용자의 입장에서 공공 오픈데이터를 활용할 때 고려해야 할 사항들로 데이터 공개 시 데이터에 대한 명확한 설명 제시, 데이터 생애주기에 걸쳐 양질의 데이터 생산 및 공개, 데이터 발행자와 이용자 간의 지속적인 커뮤니케이션을 제언하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.27-30
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• 2021

경제 성장과 함께 자동차의 수요가 늘어남에 따라 교통사고 발생 빈도는 꾸준히 증가하고 있다. 이에, 본 연구에서는 교통사고를 야기하는 도로 및 기상환경과 같은 조건을 활용하여 기계학습 모델을 통해 서울시 교통사고 사상자 수를 예측하는 모형을 찾고자 한다. 활용한 데이터는 도로교통 공단에서 제공하는 교통사고 사상자 수 정보를 포함하는 데이터로 2015년부터 2018년도까지 데이터를 학습에 사용하였고 2019년도 데이터를 테스트 평가에 사용하였다. 실증연구를 통해 트리 기반의 모델 별 성능을 비교하였으며 본 연구에 대한 결과는 사고 발생 시 우선순위에 의한 구조활동이 가능하게 함과 도로상황 및 기상을 고려한 안전운전 가이드 지식으로 활용될 수 있다.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.143-149
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• 2021

As the need to establish a big data system for rapid provision of big data and efficient management of resources has emerged due to rapid entry into the hyper-connected intelligence information society, public institutions are pushing to establish a big data system. Therefore, this study analyzed and combined the success factors of big data-related studies and the specific aspects of big data in public institutions based on the measurement of environmental factors for establishing an integrated information system for higher education institutions. In addition, 19 measurement items reflecting big data characteristics were derived from big data experts using brainstorming and Delphi methods, and a plan to successfully apply them to public institutions that want to build big data systems was proposed. We hope that this research results will be used as a foundation for the successful establishment of big data systems in public institutions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.305-306
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• 2024

본 논문에서는 도커와 쿠버네티스를 활용하여 미세먼지 데이터를 수집할 때 다량으로 늘어나는 데이터를 효율적으로 수집하고 관리하기 위한 방안을 제시한다. 도커 이미지는 작성된 Dockerfile을 통해 생성되며, 필요한 의존성과 설정이 반영되어 있다. 쿠버네티스를 이용하여 생성된 도커 이미지를 기반으로 컨테이너를 생성하고, 컨테이너들을 파드 내에서 실행함으로써 데이터를 효율적으로 수집하고 관리한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.512-515
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• 2018

웹의 발달로 많은 양의 데이터를 손쉽게 접할 수 있지만, 이러한 데이터들로 얼마나 의미 있는 정보를 잘 끌어내어 공개하고 얼마나 잘 활용시키느냐가 중요한 이슈가 되었다. 본 연구에서는 각각의 자원들이 연결된 데이터 중심의 웹을 구성하기 위해 대구시에서 제공하는 공공데이터를 이용하여 링크드 데이터를 구축한다. 수집한 데이터에서 제공하는 정보를 바탕으로 맛집에 대한 온톨로지를 구축하여 데이터를 발행하고, SPARQL을 활용한 간단한 웹 어플리케이션을 구현한다.