• Title/Summary/Keyword: 공공 빅데이터

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FAIR Principle-Based Metadata Assessment Framework (FAIR 원칙 기반 메타데이터 평가 프레임워크)

  • Park, Jin Hyo;Kim, Sung-Hee;Youn, Joosang
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.12
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    • pp.461-468
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    • 2022
  • Development of the big data industry, the cases of providing data utilization services on digital platforms are increasing. In this regard, research in data-related fields is being conducted to apply the FAIR principle that can be applied to the assessment of (meta)data quality, service, and function to data quality evaluation. Especially, the European Open Data Portal applies an assessment model based on FAIR principles. Based on this, a data maturity assessment is conducted and the results are disclosed in reports every year. However, public data portals do not conduct data maturity evaluations based on metadata. In this paper, we propose and evaluate a new model for data maturity evaluation on a big data platform built for multiple domestic public data portals and data transactions, FAIR principles used for data maturity evaluation in Europe's open data portals. The proposed maturity evaluation model is a model that evaluates the quality of public data portal datasets.

Domestic Market and Economic Impact of the Re-use of PSI(Public Sector Information) (공공정보 민간활용 시장 및 파급효과)

  • Heo, P.S.;Park, G.M.;Park, W.J.;Cho, G.S.;Ryu, W.
    • Electronics and Telecommunications Trends
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    • v.28 no.4
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    • pp.118-131
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    • 2013
  • 최근 과학 및 IT 패러다임은 HW(과거) 및 SW(현재) 중심에서 '데이터 빅뱅'을 활용하여 정치 사회 경제 등 제반 이슈와 연계된 분석 예측으로 진화 중이다. 국가안전 및 위험관리, 의료, 교육, 복지, 환경 등 사회 전반에 걸쳐 공공부문에서의 빅데이터 활용 가능성이 높아지고 있다. 공공정보 자체뿐만 아니라 민간정보와의 통합 분석을 통해 효과적인 맞춤형 정책과 새로운 지식정보 서비스 제공이 가능하기 때문에 주요 선진국은 공공정보의 적극 활용을 위해 다양한 정책을 경쟁적으로 추진해 오고 있다. 공공정보의 민간활용 촉진은 정보 제공자인 공공기관뿐만 아니라, 이를 활용하는 민간 사업자, 관련 서비스 사용자 모두에게 경제적 비경제적 가치를 제공할 수 있다. 따라서, 본 연구를 통해 국내 공공정보 민간활용 산업의 경제적 파급효과를 추정하고, 중요한 전 후방 연결 산업들을 파악하고자 한다.

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A Case Study of Basic Data Science Education using Public Big Data Collection and Spreadsheets for Teacher Education (교사교육을 위한 공공 빅데이터 수집 및 스프레드시트 활용 기초 데이터과학 교육 사례 연구)

  • Hur, Kyeong
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.459-469
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    • 2021
  • In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

Case Study on Public Document Classification System That Utilizes Text-Mining Technique in BigData Environment (빅데이터 환경에서 텍스트마이닝 기법을 활용한 공공문서 분류체계의 적용사례 연구)

  • Shim, Jang-sup;Lee, Kang-wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.1085-1089
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    • 2015
  • Text-mining technique in the past had difficulty in realizing the analysis algorithm due to text complexity and degree of freedom that variables in the text have. Although the algorithm demanded lots of effort to get meaningful result, mechanical text analysis took more time than human text analysis. However, along with the development of hardware and analysis algorithm, big data technology has appeared. Thanks to big data technology, all the previously mentioned problems have been solved while analysis through text-mining is recognized to be valuable as well. However, applying text-mining to Korean text is still at the initial stage due to the linguistic domain characteristics that the Korean language has. If not only the data searching but also the analysis through text-mining is possible, saving the cost of human and material resources required for text analysis will lead efficient resource utilization in numerous public work fields. Thus, in this paper, we compare and evaluate the public document classification by handwork to public document classification where word frequency(TF-IDF) in a text-mining-based text and Cosine similarity between each document have been utilized in big data environment.

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For airline preferences of consumers Big Data Convergence Based Marketing Strategy (소비자의 항공사 선호도에 대한 빅데이터 융합 기반 마케팅 전략)

  • Chun, Yong-Ho;Lee, Seung-Joon;Park, Su-Hyeon
    • Journal of Industrial Convergence
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    • v.17 no.3
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    • pp.17-22
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    • 2019
  • As the value of big data is recognized as important, it is possible to advance decision making by effectively introducing and improving the development and utilization of JAVA and R programs that can analyze vast amounts of existing and unstructured data to governments, public institutions and private businesses. In this study, news data was collated and analyzed through text mining techniques in order to establish marketing strategies based on consumers' airline preferences. This research is meaningful in establishing marketing strategies based on analysis results by analyzing consumers' airline preferences using high-level big data utilization program techniques for data that were difficult to obtain in the past.

Analysis of Encryption Algorithm Performance by Workload in BigData Platform (빅데이터 플랫폼 환경에서의 워크로드별 암호화 알고리즘 성능 분석)

  • Lee, Sunju;Hur, Junbeom
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.6
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    • pp.1305-1317
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    • 2019
  • Although encryption for data protection is essential in the big data platform environment of public institutions and corporations, much performance verification studies on encryption algorithms considering actual big data workloads have not been conducted. In this paper, we analyzed the performance change of AES, ARIA, and 3DES for each of six workloads of big data by adding data and nodes in MongoDB environment. This enables us to identify the optimal block-based cryptographic algorithm for each workload in the big data platform environment, and test the performance of MongoDB by testing various workloads in data and node configurations using the NoSQL Database Benchmark (YCSB). We propose an optimized architecture that takes into account.

Service-oriented Public Organizations and Human Resources Based on Enterprise-wide Big Data (전사적 빅데이터를 활용한 서비스 중심적 공공 조직 및 인사 관리 방안)

  • Jeonghee Choi;Seunguk Park
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.361-362
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    • 2023
  • 본 연구는 공공 조직 및 인사 관리의 새로운 패러다임으로서 서비스 중심적 접근법을 제시하였다. 특히 코로나19 팬데믹 이후의 불확실하고 경쟁적인 환경에서는 파편화된 데이터를 마이크로 서비스화하고 동적으로 재조합하는 것이 중요하며, 이를 실현하기 위한 모델로 KISTI의 ScienceON API Gateway와 시나리오 활용 서비스를 참고하였다. 이러한 접근법은 조직 및 인사 관리의 투명성과 효율성을 높이며, 서비스-이용자 간 상호작용을 강화하고, 조직의 변화를 촉진하는 데 기여할 것으로 기대된다.

An Empirical Study on the Effects of Top Management Leadership for Big Data Success (빅데이터 성공에 최고경영층 리더십이 미치는 영향: 실증연구)

  • Park, Sohyun;Koo, Bonjae;Lee, Kukhie
    • Information Systems Review
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    • v.18 no.2
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    • pp.39-57
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    • 2016
  • Previous studies on the success factors of big data implementation have called for future research and further examination of the top management leadership's impact. This research proposes and empirically tests three hypotheses, including how top management leadership can directly affect big data investment, how it can mediate the causal relationship between big data investment and idea usefulness, and how it can mediate the relationship between idea usefulness and business utilization. Based on the data collected from 108 big data users in Korean companies, we determined that all three hypotheses are statistically significant. By shedding light on top management leadership and its characteristics, we can provide better suggestions on what needs to be done to ensure the success of big data.