• Journal of Information Science Theory and Practice
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• 제9권3호
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• pp.14-30
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• 2021

Data innovation is at the core of the Fourth Industrial Revolution. While the catastrophic COVID-19 pandemic has accelerated the societal shift toward a data-driven society, the direction of overall data regulation remains unclear and data policy experts have yet to reach a consensus. This study identifies and examines the ideal regulator models of data-policy experts and suggests an appropriate method for developing policy in the data economy. To identify different typologies of data regulation, this study used Q methodology with 42 data policy experts, including public officers, researchers, entrepreneurs, and professors, and additional focus group interviews (FGIs) with six data policy experts. Using a Q survey, this study discerns four types of data policy regulators: proactive activists, neutral conservatives, pro-protection idealists, and pro-protection pragmatists. Based on the results of the analysis and FGIs, this study suggests three practical policy implications for framing a nation's data policy. It also discusses possibilities for exploring diverse methods of data industry regulation, underscoring the value of identifying regulatory issues in the data industry from a social science perspective.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1192-1201
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• 2021

This study focused on how to analyze the ICT policy formation process using social big data. Specifically, in this study, a method for quantifying variables that influenced policy formation using the concept of a policy triggering mechanism and elements necessary to present the analysis results were proposed. For the analysis of the ICT policy triggering mechanism, variables such as 'Scope', 'Duration', 'Interactivity', 'Diversity', 'Attention', 'Preference', 'Transmutability' were proposed. In addition, 'interpretation of results according to data level', 'presentation of differences between collection and analysis time points', and 'setting of garbage level' were suggested as elements necessary to present the analysis results.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2015년도 제51차 동계학술대회논문집 23권1호
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• pp.281-282
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• 2015

Data, by itself, will not reveal the optimal policy choice. Nor will data alone tell us what problems to focus on or how to direct resources. It should be recognized upfront that data-driven policy making cannot provide all the answers to the challenges of good governance. Policy decisions always depend on a combination of facts, analysis, judgment, and values. In this paper, we research on factors to design an organizational policy making for Big Data.

• 한국컴퓨터정보학회논문지
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• 제21권2호
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• pp.1-7
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• 2016

In this paper, we propose in this paper present a novel locality data allocation policy as COLD(Correlated Locality Data) allocation policy. COLD is defined as a set of data that will be updated together later. By distributing a COLD into a NAND block separately, it can preserve th locality. In addition, by handling multiple COLD simultaneously, it can obtain the parallelism among NAND chips. We perform two experiment to demonstrate the effectiveness of the COLD data allocation policy. First, we implement COLD detector, and then, analyze a well-known workload. And we confirm the amount of COLD found depending on the size of data constituting the COLD. Secondly, we compared the traditional page-level mapping policy and COLD for garbage collection overhead in actual development board Cosmos OpenSSD. Experimental results have shown that COLD data allocation policy is significantly reduces the garbage collection overhead. Also, we confirmed that garbage collection overhead vary depending on the COLD size.

• 공학교육연구
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• 제22권5호
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• pp.37-48
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• 2019

The government has tried to develop a platform for systematically collecting and managing engineering education data for policy proposals. However, there have been few cases of big data analysis platform for policy proposals in engineering education, and it is difficult to determine the major function of the platform, the purpose of using big data, and the method of data collection. This study aims to collect the cases of big data analysis systems for the development of a big data system for educational policy proposals, and to conduct a study to analyze cases using the analysis frame of key elements to consider in developing a big data analysis platform. In order to analyze the case of big data system for engineering education policy proposals, 24 systems collecting and managing big data were selected. The analysis framework was developed based on literature reviews and the results of the case analysis were presented. The results of this study are expected to provide from macro-level such as what functions the platform should perform in developing a big data system and how to collect data, what analysis techniques should be adopted, and how to visualize the data analysis results.

• 한국정보과학회논문지:데이타베이스
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• 제31권1호
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• pp.1-12
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• 2004

최근 네트워크 구성이 복잡해짐에 따라 정책기반의 네트워크 관리기술에 대한 필요성이 증가하고 있으며, 특히 네트워크 보안관리를 위한 새로운 패러다임으로 정책기반의 네트워크 관리 기술이 도입되고 있다. 보안정책 서버는 새로운 정책을 입력하거나 기존의 정책을 수정, 삭제하는 기능과 보안정책 결정 요구 발생시 정책결정을 수행하여야 하는데 이를 위해서는 보안정책 실행시스템에서 보내온 경보 메시지에 대한 분석 및 관리가 필요하다. 따라서 이 논문에서는 정책기반 네트워크 보안관리 프레임워크의 구조 중에서 보안정책 서버의 효율적인 보안정책 수립 및 수행을 지원하기 위한 경보데이타 분석기를 설계하고 구현한다. 경보 데이타 저장과 분석을 위해서 데이타베이스 스키마를 설계하고 저장된 경보데이타를 분석하는 모듈을 구현하며 경보데이타 마이닝 엔진을 구현하여 경보데이타를 효율적으로 분석하고 이를 통해 경보들의 새로운 유사패턴그룹이나 공격시퀀스를 유추하여 능동적인 보안정책관리를 지원할 수 있도록 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2768-2780
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• 2019

Ciphertext-policy attribute-based encryption (CP-ABE) is one of the practical technologies to share data over cloud since it can protect data confidentiality and support fine-grained access control on the encrypted data. However, most of the previous schemes only focus on data confidentiality without considering data receiver privacy preserving. Recently, Li et al.(in TIIS, 10(7), 2016.7) proposed a CP-ABE with hidden access policy and testing, where they declare their scheme achieves privacy preserving for the encryptor and decryptor, and also has high decryption efficiency. Unfortunately, in this paper, we show that their scheme fails to achieve hidden access policy at first. It means that any adversary can obtain access policy information by a simple decisional Diffie-Hellman test (DDH-test) attack. Then we give a method to overcome this shortcoming. Security and performance analyses show that the proposed scheme not only achieves the privacy protection for users, but also has higher efficiency than the original one.

• 대한원격탐사학회지
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• 제15권4호
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• pp.329-337
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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-widely. Korea will also be able to take full advantage of the satellite data once the Korea Multi-Purpose Satellite 1 (KOMPSAT-l) 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 instruments. 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. 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.

• 보건행정학회지
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• 제21권1호
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• pp.77-92
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• 2011

Objectives : This study examined the health policy researchers' needs and their accessibility towards health insurance claim datasets according to their academic capacity. Methods : An online questionnaire to capture relevant proxy variables for academic needs, accessibility, and research capacity was constructed based on previous studies. The survey was delivered to active health policy researchers through three major scholarly associations in South Korea. Seven-hundred and one scholars responded while the survey as open for 12 days (starting on December 20th, 2010). Descriptive statistics and logistic regression analysis were carried out. Results : Regardless of the definition for operational needs, the prevalent needs of survey respondents were not met with the current provision of claim data. Greater research capacity was shown to be correlated with increased demand for claim data along with a positive correlation between attempts to obtain claim datasets and research capacity. A greater research capacity, however, was not necessarily correlated with better accessibility to the claim data. Conclusions : The substantial unmet need for claim data among the healthcare policy research community calls for establishing proactive institutions which could systematically prepare and make available public datasets and provide call-in services to facilitate proper handling of data.

• 한국콘텐츠학회논문지
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• 제18권10호
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• pp.229-235
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• 2018

본 연구의 목적은 효율적이고 효과적인 정책 발굴 과정에서 빅데이터의 활용이 점차 중요해지는 현실에서 지방자치단체의 정책 이슈 발굴에 빅데이터 분석을 활용하는 방안을 제시하는 데 있다. 이를 위하여 본 연구에서는 수원시를 대상으로 지난 3년간의 수원시 약 18만 건의 기사를 분석하여 정책 이슈를 발굴하였으며, 이를 IPA분석을 통해 정책의 우선순위를 평가하였다. 본 연구의 분석 결과는 신문 기사를 통한 반정형 빅데이터의 분석으로 전국의 주요 이슈와는 차별화된 지방자치단체의 차별화된 정책 이슈를 도출하는데 효과적임을 보였으며, 특히 도출된 정책 이슈들이 대부분 그 우선순위가 높은 것으로 평가되었다. 이처럼 본 연구에서 제시한 빅데이터 분석을 통한 정책 이슈 발굴의 방법론은 지방자치단체가 효율적인 정책 이슈를 도출하고 민의를 효과적으로 파악할 수 있음을 의미한다. 또한, 본 연구에서 제시한 방법론은 지방자치단체의 온라인 민원 자료, 주민 SNS 등 다양한 반정형, 비정형 빅데이터의 분석을 통한 정책 이슈 발굴에 적용이 가능할 것으로 기대된다.