• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.161-179
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• 2007

As increasingly diverse kinds of information materials are available on the Internet, it becomes a challenge to define an adequate level of metadata provision for each different type of material in the context of digital libraries. This study explores issues of metadata provision for a particular type of material, statistical tables. Statistical data always involves numbers and numeric values which should be interpreted with an understanding of underlying concepts and constructs. Because of the unique data characteristics, metadata in the statistical domain is essential not only for finding and discovering relevant data, but also for understanding and using the data found. However, in statistical metadata research, more emphasis has been put on the question of what metadata is necessary for processing the data and less on what metadata should be presented to users. In this study, a case study was conducted to gauge the status of metadata provision for statistical tables on the Internet. The websites of two federal statistical agencies in the United States were selected and a content analysis method was used for that purpose. The result showing insufficient and inconsistent provision of metadata demonstrate the need for more discussions on statistical metadata from the ordinary web users' perspective.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.151-159
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• 2019

As the era of big data, which is the foundation of the fourth industry, has come, most related industries are developing related solutions focusing on the technologies of data storage, statistical analysis and visualization. However, for the diffusion of bigdata technology, it is necessary to develop the prediction analysis technologies using artificial intelligence. But these advanced technologies are only possible by some experts now called data scientists. For big data-related industries to develop, a non-expert, called a citizen data scientist, should be able to easily access the big data analysis process at low cost because they have insight into their own data. In this paper, we propose a system for analyzing bigdata and building business models with the support of easy-to-use analysis system without knowledge of high-level data science. We also define the necessary components and environment for the prediction analysis system and present the overall service plan.

• Informatization Policy
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• v.30 no.2
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• pp.46-67
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• 2023

There are criticisms that, despite the proactive government policy on open government data (hereinafter "open data"), certain highly demanded data remains restricted due to legal constraints. In this study, we aim to analyze the factors that limit the opening and utilization of open data, focusing on cases wherein requests for open data provision have been denied. We will explore possible approaches that are in harmony with the Open Data Law while examining the constitutional value of open data, considering the foundational Open Data Charter that underpins the government's data policy. We will also examine cases wherein requests for data provision have been denied for institutional reasons, with nearly half of these cases involving open data that includes personal information. It is necessary to explore the potential for improvement in these cases. Furthermore, considering the recent amendment to the Personal Information Protection Act, which allows for the processing of pseudonymous information without the consent of the data subject for limited purposes, it is an opportune time to consider the need for amending the Open Data Law to facilitate broader access and utilization of open data for the nation. Lastly, we will propose institutional improvement directions aligned with the opening and utilization of open data by examining the constraints of and need for improvement in the selected target laws.

• Journal of the Korean Society for information Management
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• v.41 no.3
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• pp.381-409
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• 2024

In co-authorship networks, temporal networks can be modeled by identifying the formation and dissolution (linking and removing) of co-authorship relationships over time from the publication year information of the papers. Therefore, this study seeks to analyze the overall research collaboration networks of data papers and articles from an evolutionary perspective for modeling the temporal network in terms of informetrics and investigating the dynamic and structural mechanisms of the temporal co-authorship network. For that purpose, Biodiversity Data Journal, a mixed data journal in the biodiversity domain was used as the unit of analysis in this study as this domain had proposed data paper as a new mechanism for data publication. In addition, bibliometric records of 247 data papers and 638 articles involving two or more researchers were collected from the Web of Science. The results indicated that the dynamic co-authorship networks of data papers and articles in the biodiversity domain exhibited the scale-free property of a complex network and the small-world property in the Watts-Strogatz sense during the network evolution. Also, both publication types kept the structure of locally cohesive author groups over time in the networks. The implementation of TTBC (Temporal Triadic Betweenness Centrality) has allowed for the examination and tracking of the evolutionary trends of important or influential time-dependent authors (nodes) by the target year. And last, visualization with a dynamic approach enabled a more effective identification of analysis results, such as the exhibited structural difference in the temporal co-authorship networks of data papers and articles in the biodiversity domain, which can be interpreted as the structural properties of the networks among collaborative researchers dealing with data.

• Journal of Korean Library and Information Science Society
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• v.41 no.4
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• pp.151-170
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• 2010

There is a growing interest in user-centered classification or reader-interest classification, as questions have arisen from the meanings and the effects of traditional library classification. American public libraries have used fiction genre classification called bookstore model as an alternative to the traditional classification schemes. As a result, accessibility to the collection was promoted and library service for their users was improved. This study intends to make a comprehensive inquiry about the philosophical background and functional features of genre classification. To the end, literature survey and interviews or e-mails with librarians in American public libraries were conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.440-446
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• 2016

Military secrets or confidential data of any organization are extremely important assets. They must be discluded from outside. To do this, methods for detecting anomalous attacks and intrusions inside the network have been proposed. However, most anomaly-detection methods only cover aspects of intrusion from outside and do not deal with internal leakage of data, inflicting greater damage than intrusions and attacks from outside. In addition, applying conventional anomaly-detection methods to data exfiltration creates many problems, because the methods do not consider a number of variables or the internal network environment. In this paper, we describe issues considered in data exfiltration detection for anomaly detection (DEDfAD) to improve the accuracy of the methods, classify the methods as profile-based detection or machine learning-based detection, and analyze their advantages and disadvantages. We also suggest future research challenges through comparative analysis of the issues with classification of the detection methods.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.43-55
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• 2020

Recently, as the importance of experience data increases, there are many attempts to deal with experience data from a data science perspective. In the case of approaching as a collection method of a quantitative survey method that seeks to quantify numerically such as big data, it is difficult to interpret the value of experience in a wide range, and it is relatively expensive and time consuming, and personal information infringement There is a limit to the analysis due to the risk of However, since ethnography, a procedure for collecting experience data based on qualitative research, is mainly carried out in the natural real environment of future customers from the perspective of users, it is possible to confirm the nature that customers face with a small sample. In addition, it is also easy to interpret the relational dimension of the empirical data. Although the ethnography method of collecting experiential data is economical and efficient, it is important to reduce errors in the collection process because the lack of scientific procedures for the data collection process can be a problem. It is important to secure the validity of whether the correct measurement tool is used for ethnography-based experiential data collection and to secure the reliability of the use of a valid measurement tool and method by accurately selecting the measurement target. From this point of view, it is necessary to verify the reliability of the research method that clearly selects the measurement target and secures the validity for the development of the correct measurement method and tool for the collection of ethnography experience data. Therefore, in this study, a verification study was conducted on the data and methodology cases of the'I know you_AI' service that analyzes the customer experience of self-employed based on the ethnography method of collecting experience data..

• Journal of Technology Innovation
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• v.31 no.1
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• pp.65-103
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• 2023

With the recent surge in the share of data-based economic activities, there have been vibrant discussions on the data economy. Yet, few extant works provide a framework for systematically analyzing the transition to the data economy by major industries in Korea. By reviewing the existing literature, we first summarize the main characteristics of the data economy as building platforms, the greater importance of predictive power, and the increased use of new analytics. Next, based on such understanding, we provide a comparative analysis regarding the degree of data-based activities in Korea's financial, real estate, and medical sectors. We find that the speed at which, and the content of the data economy characteristics being realized were different for the different sectors. These findings suggest that differentiated policy approaches by major industrial sectors such as finance, real estate, and medical care are needed to improve economic productivity and increase welfare through the spread of the data economy.

• Journal of Industrial Convergence
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• v.18 no.6
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• pp.19-25
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• 2020

Big data analytics are indispensable today in various industries and public sectors. Therefore, in this study, we will utilize big data analysis to search for improvement plans for domestic tourism services using the LDA analysis method. In particular, we have tried an exploratory approach that can improve tourist satisfaction, which can improve revisit and service, especially in Seoul, which has the largest number of foreign tourists. In this study, we collected and analyzed statistical data of Seoul City and Korea Tourism Organization and Internet information such as SNS via R. And we utilized text mining methods including LDA. As a result of the analysis, one of the purposes of visiting South Korea by foreigners was gastronomic tourism. We will try to derive measures to improve the quality of services centered on gastronomic tourism.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.11-23
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• 2022

Collaboration tools are used widely as non-face-to-face work increases due to social distancing after COVID-19. The tools are being developed in a cross-platform manner with 'Electron', an open source framework based on Chromium, to ensure accessibility on multiple devices. Electron Apps, applications built with Electron framework, store data in a manner similar to Chromium-based web browsers, so the data can be acquired in the same way as the data is acquired from a web browser. In this paper we analyze the data structure of web storage and suggest a method to get the message from Electron Apps focused on collaboration tools such as Jandi, Slack, and Microsoft Teams. For Jandi, we get the message from Cache by using previously developed tools, and in the case of Slack and Microsoft Teams, we get the message from IndexedDB by using the message carving tool we developed.