• 제목/요약/키워드: data policy

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개인정보 처리방침(Privacy Policy) 공개에 관한 주요 4개국 법제 비교분석 (A Comparative Analysis of the Legal Systems of Four Major Countries on Privacy Policy Disclosure)

  • 정태철;권헌영
    • 한국IT서비스학회지
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    • 제22권6호
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    • pp.1-15
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    • 2023
  • This study compares and analyzes the legal systems of Korea, the European Union, China, and the United States based on the disclosure principles and processing policies for personal data processing and provides references for seeking improvements in our legal system. Furthermore, this research aims to suggest institutional implications to overcome data transfer limitations in the upcoming digital economy. Findings on a comparative analysis of the relevant legal systems for disclosing privacy policies in four countries showed that Korea's privacy policy is under the eight principles of privacy proposed by the OECD. However, there are limitations in the current situation where personal information is increasingly transferred overseas due to direct international trade e-commerce. On the other hand, the European Union enacted the General Data Protection Regulation (GDPR) in 2016 and emphasized the transfer of personal information under the Privacy Policy. China also showed differences in the inclusion of required items in its privacy policy based on its values and principles regarding transferring personal information and handling sensitive information. The U.S. CPRA amended §1798.135 of the CCPA to add a section on the processing of sensitive information, requiring companies to disclose how they limit the use of sensitive information and limit the use of such data, thereby strengthening the protection of data providers' rights to sensitive information. Thus, we should review our privacy policies to specify detailed standards for the privacy policy items required by data providers in the era of digital economy and digital commerce. In addition, privacy-related organizations and stakeholders should analyze the legal systems and items related to the principles of personal data disclosure and privacy policies in major countries so that personal data providers can be more conveniently and accurately informed about processing their personal information.

Policy Direction for Promoting the Satellite Data Use in Public Sector

  • Kim, Young-Pyo;Sakong, Hosang;Park, Sung-Mi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.355-362
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    • 1999
  • With the ready access to the high resolution satellite image data, users of and areas covered by satellite image data are constantly on the rise world-wide. Korea will also be able to take full advantage of the satellite data once the KOMPSAT is successfully launched. Harmonizing satellite data production and application technology and users' needs, along with the guiding policy is essential for promoting satellite data use. Up to now, the Korean government has mainly concentrated on developing production technology for the satellite units. However, the imminent task of independent satellite data production demands a promotion policy for satellite data use. In this context, the policy is defined as an important medium for identifying the role and status of satellite image information at the national level and also Preparing the legal as well as systematic foundation for producing, building, distributing, and packaging satellite data. For example, in the countries with the advanced satellite technology, such as the United States, the United Kingdom, and Australia, digital ortho image and digital elevation model (DEM) are mandatorily included in the National Geographic Framework Data through policy measures. In addition, in order for the efficient provision of the satellite data, separate organization or agency is being in operation for the exclusive production and distribution of the satellite data. The present paper aims to examine the role and status of the satellite data as well as their current status and problems in Korea in reference to the National Spatial Data Infrastructure, and finally to provide the policy directions to promote the satellite data use in public sector on the basis of the preceding analyses.

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공공데이터 개방 정책이 공공 혁신에 미치는 영향에 관한 연구 (The Influence of Open Data Policies on Public Innovation)

  • 임준원;최경현
    • 대한산업공학회지
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    • 제43권1호
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    • pp.19-29
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    • 2017
  • Nowadays, the policy of open data disclosure has become one of the globally used tools for public innovation. For this reason, this study investigates whether the policy has eventually created the achievement of public innovation in Korea. To this end, this study evaluates qualities of the fourteen thousand open data in Korea that is disclosed to the public and compares it with indexes such as the usage of data, transparency index, and Government 3.0 Excellency Index, which are regarded as the outcome of the disclosure. Based on the result, this study aims to suggest future orientation for the policy.

Data Mining for Knowledge Management in a Health Insurance Domain

  • Chae, Young-Moon;Ho, Seung-Hee;Cho, Kyoung-Won;Lee, Dong-Ha;Ji, Sun-Ha
    • 지능정보연구
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    • 제6권1호
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    • pp.73-82
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    • 2000
  • This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

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Big Data Strategies for Government, Society and Policy-Making

  • LEE, Jung Wan
    • The Journal of Asian Finance, Economics and Business
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    • 제7권7호
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    • pp.475-487
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    • 2020
  • The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

A Big Data-Driven Business Data Analysis System: Applications of Artificial Intelligence Techniques in Problem Solving

  • Donggeun Kim;Sangjin Kim;Juyong Ko;Jai Woo Lee
    • 한국빅데이터학회지
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    • 제8권1호
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    • pp.35-47
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    • 2023
  • It is crucial to develop effective and efficient big data analytics methods for problem-solving in the field of business in order to improve the performance of data analytics and reduce costs and risks in the analysis of customer data. In this study, a big data-driven data analysis system using artificial intelligence techniques is designed to increase the accuracy of big data analytics along with the rapid growth of the field of data science. We present a key direction for big data analysis systems through missing value imputation, outlier detection, feature extraction, utilization of explainable artificial intelligence techniques, and exploratory data analysis. Our objective is not only to develop big data analysis techniques with complex structures of business data but also to bridge the gap between the theoretical ideas in artificial intelligence methods and the analysis of real-world data in the field of business.

미정부의 빅데이터를 위한 보안정책 (The Security Policy for Big data of US Government)

  • 홍진근
    • 디지털융복합연구
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    • 제11권10호
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    • pp.403-409
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    • 2013
  • 본 논문은 미국 정부의 빅데이터 정책과 보안 이슈에 관해 고찰하였다. 빅데이터 R&D 이니셔티브 전략과 계획, NITRD 프로그램, 정부기관의 빅데이터 전략을 소개하였고, 또한 미군에서 빅데이터 운용환경, 군사 작전에 사용되는 빅데이터 정보, 주요 연구기관과 주제, 보안가이드라인 등에 대해 살펴보았다.

데이터기반 의사결정을 위한 정책 및 사업 속성 분류체계 개발 연구 (A Study on Development of Policy Attributes Taxonomy for Data-based Decision Making)

  • 김사랑
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권3호
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    • pp.1-34
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    • 2020
  • Purpose Due to the complexity of policy environment in modern society, it is accepted as common basics of policy design to mix up a variety of policy instruments aiming the multiple functions. However, under the current situation of written-down policy specification, not only the public officers but also the policy researchers cannot easily grasp such frameworks as policy portfolio. The purpose of this study is to develop "Policy Attributes Taxonomy" identifying and classifying the public programs to help making decisions for allocative efficiency with effectiveness-based information. Design/methodology/approach To figure out the main scheme and classification criteria of Policy Attributes Taxonomy which represents characteristics of public policies, previous theories and researches on policy components were explored. In addition, to test taxonomic feasibility of certain information system, a set of "Feasibility Standards" was drawn from "requirements for well-organized criteria" of eminent taxonomy literatures. Finally, current government classification system in the area of social service was tested to visualize the application of Taxonomy and Standards. Findings Program Taxonomy Schemes were set including "policy goals", "policy targets", "policy tools", "logical relation" and "delivery system". Each program and project could be condensed into these attributes, making their design more easily distinguishable. Policy portfolio could be readily made out by extracting certain characteristics according to this scheme. Moreover, this taxonomy could be used for rearrangement of present "Program Budget System" or estimation of "Basic Income".

연구데이터 레포지터리의 데이터 접근 및 이용 통제 정책 요소에 관한 연구 (A Study on Policy Components of Data Access and Use Controls in Research Data Repositories)

  • 김지현
    • 한국도서관정보학회지
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    • 제47권3호
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    • pp.213-239
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    • 2016
  • 전 세계적으로 오픈 데이터가 강조되는 환경에서 데이터의 공유 및 재이용으로 인해 발생하는 문제점을 최소화하기 위한 정책적 논의도 함께 진행되고 있다. 본 연구에서는 연구데이터 레포지터리에서 데이터의 접근 및 이용을 통제하는 정책요소들을 조사하고 학문 분야별로 그러한 정책 요소들의 공통점과 차이점을 살펴보는 것을 목적으로 하였다. 이를 위해 해외 연구데이터 레포지터리 37곳을 대상으로 데이터 접근 및 이용 통제를 규정하고 있는 정책 요소를 분석하였다. 생명과학 및 보건과학분야 20개 레포지터리, 화학 지구환경과학 물리학 분야 10개 레포지터리, 사회과학 및 일반과학 분야 7개 레포지터리로 구분하여 분석을 실시한 결과 저작권 및 라이선스 규정, 데이터 인용, 면책조항 및 엠바고 적용 관련 규정이 공통적으로 제시되는 정책 요소인 것으로 나타났다. 그러나 분야별로 규정되고 있는 정책 요소의 다양성에는 차이가 있는 것으로 나타났으며 이는 분야별로 강조되는 데이터 접근 및 이용 통제 근거의 차이를 반영하는 것으로 볼 수 있다.

Incidence of Online Public Opinion on Guangzhou Simultaneous Renting and Purchasing Policy - A data mining application

  • Wang, Yancheng;Li, Haixian
    • Asian Journal for Public Opinion Research
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    • 제5권4호
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    • pp.266-284
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    • 2018
  • This paper adopts the big data research method, and draws 491 data from the Tianya Forum about the Simultaneous Renting and Purchasing policy of Guangzhou. The qualitative analysis software Nvivo11 is used to cluster the main questions about the Simultaneous Renting and Purchasing policy in the forum. The 36 high-frequency word frequencies are obtained through text clustering. Through rooted theory analysis, the main driving factors for summarizing people's doubts are 9 main categories, 3 core categories, and the model of driving factors for online forums is established. The study finds that resource factors are the most key factor, economic factors are the important drivers, and policy guiding factors are sub-important drivers.