• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.287-304
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• 2020

There have been a number of legal & policy studies on the affecting factors of big data utilization, but empirical research on the composition factors of personal information regulation or data combination, which acts as a constraint, has been hardly done due to the lack of relevant statistics. Therefore, this study empirically explores the priority of personal information regulation factors and data combination factors that influence big data utilization through Delphi Analysis. As a result of Delphi analysis, personal information regulation factors include in order of the introduction of pseudonymous information, evidence clarity of personal information de-identification, clarity of data combination regulation, clarity of personal information definition, ease of personal information consent, integration of personal information supervisory authority, consistency among personal information protection acts, adequacy punishment intensity in case of violation of law, and proper penalty level when comparing EU GDPR. Next, data combination factors were examined in order of de-identification of data combination, standardization of combined data, responsibility of data combination, type of data combination institute, data combination experience, and technical value of data combination. These findings provide implications for which policy tasks should be prioritized when designing personal information regulations and data combination policies to utilize big data.

• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.161-181
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• 1994

As information technologies are applied to the libraries in information society, the library services have been changing its feature. Therefore, the purpose of this paper is to explore and to establish a paradigm of the library services in information society. It is hypothesized that the application of information technologies leads to the change of the library services in information society. To prove the hypothesis, the data were collected from various research results carried out in the developed countries and by observing various libraries where the information technologies are extensively applied. The findings are as follows: 1. As information technologies are applied to the library, many new library services emerge for the society. 2. As the electronic data replace the paper data, the collection of a library becomes the collection of the libraries in the world. Therefore, the accessibility to the information network is more important than to own information in the library. Librarians select various electronic data according to the library policy which distinguishes their own library collection from others. The policy also solves the various problems related to weeding and preserving library collection. And the use of CD-ROM selection tools enable library users to select their own data. Now, the censorship becomes the concems of the library users, not the library. 3. The catalogs are reorganized for the electronic data for the international use. The most important information in the catalog is the location of the data and the multi access to the data are necessary. 4. As the information technologies are applied in book selection, cataloguing, information retreival and circulation, the library users are enable to service themselves in the library. And most of the routine works related to the information service are taken over by the library staffs. Professional librarians engage in user education, information marketing and fund raising. 5. Public libraries in information society serves those who have no access to the information. They help the illiterates. patients in the hospital, prisoners, and homeless in the city. Therefore, the information technologies enhance the role of librarians in professional work in the library as well as in the information society.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.179-185
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• 2018

Big Data is strictly positioning one of method to deal with problems faced with mankind, not an icon of revolution in future anymore. Application of Big Data and protection of personal information have contradictoriness. When we weight more to usage of Big Data, someone's privacy is necessarily invaded. otherwise, we care more about keeping safe of individual information, only low-level of research using Big Data can be used to accomplish public purpose. In this study, we propose a method to anonymize Big Data collected in order to investigate the problems of personal information infringement and utilize Big Data and protect personal. This will solve the problem of personal information infringement as well as utilizing Big Data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.9-11
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• 2022

In order to sustain and revitalize the fourth industrial revolution and data economy, the world's first 'data basic law' has been enacted and implemented in Korea.,However, the law prioritizes the activation of data industry and the activation of data production, distribution and use that deals with the protection of data assets, so it can be applied and interpreted more than the Personal Information Protection Act or the Copyright Act.,In this paper, the main contents of the data basic law are examined and the personal information issue is considered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2682-2700
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• 2023

To cope with the risks of climate change and promote the realization of carbon peaking and carbon neutrality, this paper first comprehensively considers the policy background, technical trends and carbon reduction paths of energy conservation and emission reduction in data center server industry. Second, we propose a computing power carbon efficiency of data center server, and constructs the carbon emission per performance of server (CEPS) model. According to the model, this paper selects the mainstream data center servers for testing. The result shows that with the improvement of server performance, the total carbon emissions are rising. However, the speed of performance improvement is faster than that of carbon emission, hence the relative carbon emission per unit computing power shows a continuous decreasing trend. Moreover, there are some differences between different products, and it is calculated that the carbon emission per unit performance is 20-60KG when the service life of the server is five years.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Journal of the Korea Society of Computer and Information
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• v.20 no.7
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• pp.1-7
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• 2015

Although data on the internet can be used in various fields such as source of data of IR(Information Retrieval), Data mining and knowledge information servece, and contains a lot of unnecessary information. The removal of the unnecessary data is a problem to be solved prior to the study of the knowledge-based information service that is based on the data of the web page, in this paper, we solve the problem through the implementation of XTractor(XPath Extractor). Since XPath is used to navigate the attribute data and the data elements in the XML document, the XPath analysis to be carried out through the XTractor. XTractor Extracts main text by html parsing, XPath grouping and detecting the XPath contains the main data. The result, the recognition and precision rate are showed in 97.9%, 93.9%, except for a few cases in a large amount of experimental data and it was confirmed that it is possible to properly extract the main text of the news.

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.6-14
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• 2020

On information markets, we can identify different relations between sellers and their customers, with some users paying with money, some paying with attention, and others paying with their personal data. For the description of these different market relations, this article introduces the notion of arity into the scientific discussion. On unary information markets, customers pay with their money; examples include commercial information suppliers. Binary information markets are characterized by one market side paying with attention (e.g., on the search engine Google) or with personal data (e.g., on most social media services) and the other market side (mainly advertisers) paying with money. Our example of a ternary market is a social media market with the additional market side of influencers. If customers buy on unary markets, they know what to pay (in terms of money). If they pay with attention or with their personal data, they do not know what they have to pay exactly in the end. On n-ary markets (n greater than 1), laws should regulate company's abuse of money and-which is new-abuse of data streams with the aid of competition (or anti-trust) laws, and by modified data protection laws, which are guided by fair use of end users' attention and data.

• Journal of Information Science Theory and Practice
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• v.10 no.1
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• pp.73-88
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• 2022

This exploratory study aims to understand the potential of log data analysis and expand its utilization in user research methods. Transaction log data are records of electronic interactions that have occurred between users and web services, reflecting information-seeking behavior in the context of digital libraries where users interact with the service system during the search for information. Two ways were used to analyze South Korea's National Digital Science Library (NDSL) log data for three days, including 150,000 data: a log pattern analysis, and log context analysis using statistics. First, a pattern-based analysis examined the general paths of usage by logged and unlogged users. The correlation between paths was analyzed through a χ² analysis. The subsequent log context analysis assessed 30 identified users' data using basic statistics and visualized the individual user information-seeking behavior while accessing NDSL. The visualization shows included 30 diverse paths for 30 cases. Log analysis provided insight into general and individual user information-seeking behavior. The results of log analysis can enhance the understanding of user actions. Therefore, it can be utilized as the basic data to improve the design of services and systems in the digital library to meet users' needs.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.112-122
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• 2022

Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.