• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.37-43
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• 2022

The fundamental basis of AI technology is learningable data. Recently, the types and amounts of data collected and produced by the government or private companies are increasing exponentially, however, verified data that can be used for actual machine learning has not yet led to it. This study discusses the conditions that data actually can be used for machine learning should meet, and identifies factors that degrade data quality through case studies. To this end, two representative cases of developing a prediction model using public big data was selected, and data for actual problem solving was collected from the public data portal. Through this, there is a difference from the results of applying valid data screening criteria and post-processing. The ultimate purpose of this study is to argue the importance of data quality management that must be most fundamentally preceded before the development of machine learning technology, which is the core of artificial intelligence, and accumulating valid data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.29-35
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• 2021

Recently, with the widespread use of the Internet of Things (IoT), the service structure has been studied to interact with various service domains. A common way to interact with other service domains is to develop the APIs needed to interact on the platform. However, to use a common method, we consider many costs and resources as APIs can increase while adding connections from other service domains. To address this issue, we propose the design and implementation of a dynamic API platform. The proposed platform can dynamically create APIs when requesting service applications, depending on the target service domain. To demonstrate the feasibility of the proposed platform, we develop a COVID-19 weekly infection status, regional infection status, and vaccination status service using dynamic APIs from the Public Data Portal using the proposed dynamic API platform and Node-RED.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.2046-2055
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• 2021

This paper analyzed the primary concerns about radiation among the Korean public with a big data analysis of questions posted at the section of "Knowledge iN" on the portal site NAVER in Korea from January 2010 to August 2020. First, we extracted questions about radiation and categorized them into the three categories with TF-IDF analysis: "Medical," "Career Counseling," and "General Interest". The "Medical" category includes questions about radiation diagnosis or treatment. The "Career Counseling" category includes questions about entering college and the prospect of finding jobs in radiation-related fields. The "General Interest" category includes questions about terminology and the basic knowledge of radiation or radioisotopes. Second, we extracted common questions for each category. Finally, we analyzed the temporal change in the numbers of questions for each category to confirm whether there is any correlation between radiation-related events and the number of questions. The analysis results demonstrate that major radiation-related events have little relevance to the number of questions except during March 2011.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.219-220
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• 2022

In order to meet the trend, construction public data are already disclosing not only data generated at the construction site but also various data ranging from inspection reports and public construction contracts through multiple portals. However, unlike the excellence of the open performance evaluated by the number of data, it is difficult to evaluate the specific level of disclosure because there is no case of analyzing the quality, ease of use, and possibility of further opening of the public construction data set. On the other hand, performance measurement is already performed using an internationally agreed evaluation method in different fields such as real estate, population, and environment. So it is essential to analyze the current status of public data openings in the construction field and to derive improvement tasks. Therefore, this study conducted a survey of researchers with the highest system utilization targeting representative public data open systems in the construction field, such as E-AIS(세움터) and KISCON. To ensure fairness and increase comparability, the questionnaire was composed using evaluation items on implementing public data conducted annually by the World Wide Web Foundation, an international non-profit organization. With these responses, we investigated the status of public data disclosure and opinions on data quality and derived tasks to improve public data disclosure in construction through the analysis of the results.

• The Korea Journal of Herbology
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• v.31 no.4
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• pp.93-100
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• 2016

Objectives : The internet is the most common method to investigate information. It is showed that 75.2% of Internet users of 20s had health information search experience. So this study is aim to understanding of interest of public about the herbal medicine using internet search query volume data.Methods : The Naver that is the top internet portal web service of the Republic of Korea has provided an Internet search query volume data from January 2007 to the current through the Naver data lab (http://datalab.naver.com) service. We have collected search query volume data which was provided by the Naver in 606 herbal medicine names and sorted the data by peak and total search volume.Results : The most frequently searched herbal medicines which has less bias and sorted by peak search volume is 'wasong (와송)'. And the most frequently searched herbal medicines which has less bias and sorted by total search volume is 'hasuo (하수오)'.Conclustions : This study is showed that the rank of interest of public about herbal medicines. Among the above herbal medicines, some herbal medicines had supply issue. And there are some other herbal medicines that had very little demand in Korean medicine market, but highly interested public. So it is necessary to monitor for these herbal medicines which is highly interested of the public. Furthermore if the reliability of the data obtained on the basis of these studies, it is possible to be utilizing herbal medicine monitoring service.

• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.255-279
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• 2020

Recently, as the range of users utilizing open data has expanded from experts to students, and general citizens, the role of open data portals has changed. In the past, portals have neglected to increase data utilization through citizen participation by focusing on the role of simple data repository, but now they tend to focus on understanding, collaboration and sharing values so that users can actively use data. To meet these social trends, open data portals need to seek ways to improve user-centered services that can encourage citizen participation. The purpose of this study is to identify the main functions for citizen participation in open data portals, to analyze the current status of open data portal user services and to suggest ways to improve them. Through the literature research, we investigated the functions provided by portal services for citizen participation, deduced the types of user services, and analyzed open data portal user services. Furthermore, we suggested user-centered public data portal services improvement plans for citizen participation.

• 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.

• Knowledge Management Research
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• v.20 no.3
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• pp.73-89
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• 2019

The purpose of this study is to investigate the current state of public Big Data in Seoul and suggest policy directions for the revitalization of Seoul's public Big Data. Big Data is perceived as innovation resources under the era of 4th Industrial revolution and Data economy. Especially, public Big Data serves a significant role in terms of universal access for citizens, startup, and enterprise compared with the private sector. Seoul reorganized a substructure of government's focus on Big Data and established organizations such as Big Data Campus and Urban Data Science Lab. Although the number of public open Data has increased in Seoul, there exists not much Data with characteristics similar to Big Data, such as volume, velocity, and value. In order to present the direction of Big Data policy in Seoul, we investigate the current status of Big Data Campus and Urban Data Science Lab operated by Seoul City. Considering the results of this study, we have proposed several directions that Seoul can use in establishing big data related strategies.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.1013-1019
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• 2021

This paper reviewed the temporal changes in the public opinions on nuclear energy in Korea with a big data analysis of nuclear energy-related articles and their comments posted on the portal site NAVER. All articles that included at least one of "nuclear energy," "nuclear power plant (NPP)," "nuclear power phase-out," or "anti-nuclear" in their titles or main text were extracted from those posted on NAVER in January 2010-December 2019. First, we performed annual word frequency analysis to identify what words had appeared most frequently in the articles. For that period, the most frequent words were "NPP," "nuclear energy," and "energy." In addition, "safety" has remained in the upper ranks since the Fukushima NPP accident. Then, we performed sentiment analysis of the pre-processed articles. The sentiment analysis showed that positive-tone articles have been reported more frequently than negativetone over the entire analysis period. Last, we performed sentiment analysis of the comments on the articles to examine the public's intention regarding nuclear issues. The analysis showed that the number of negative comments to articles each month-irrespective of positive or negative tone-was always larger than that of positive comments over the entire analysis period.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2062-2066
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• 2022

Nuclear energy sources are indispensable in cost effectively achieving carbon neutral economy, where public opinion is critical to adoption as the consequences of nuclear accident can be catastrophic. In this context, discussion on spent nuclear fuel is a prerequisite to expanding nuclear energy, as it leads to the issue of radioactive waste disposal. Given the dearth of study on spent nuclear fuel public acceptance, we use text mining and big data analysis on the news article and public comments data on Naver news portal to identify the Korean public opinion on spent nuclear fuel. We identify that the Korean public is more interested in the nuclear energy policy than spent nuclear fuel itself and that the alternative energy sources affect the position towards spent nuclear fuel. We recommend relating spent nuclear fuel issue with nuclear energy policy and environmental issues of alternative energy sources to further promote spent nuclear fuel.