• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.4
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• pp.35-55
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• 2017

The Master Data is constructed for the wide use within the institution, and it is mainly used in the enterprise. In this research, we have conducted research for the purpose of building master data on infrastructure that can be used by public institutions in the country. To do this, we analyzed individual attributes of the standard data set provided by the public data portal. Among these, we extracted standard elements that match the characteristics of the Master Data. Finally, the standardized elements are verified through the standardization system that is utilized in the country.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.201-207
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• 2021

As artificial intelligence gradually expands into jobs, iIt is necessary to nurture talents with AI literacy capabilities required for non-majors. Therefore, in this study, based on the necessity and current status of AI education, AI literacy competency improvement education was conducted for non-majors so that AI learning could be sustainable in relation to future majors. For non-majors at University D, problem-solving solutions through project-based data analysis and visualization were applied over 15 weeks, and the AI ability improvement and effectiveness of learners before and after education were analyzed and verified. As a result, it was possible to confirm a statistically significant level of positive change in the learners' data analysis and utilization ability, AI literacy ability, and AI self-efficacy. In particular, it not only improved the learners' ability to directly utilize public data to analyze and visualize it, but also improved their self-efficacy to solve problems by linking this with the use of AI.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.758-759
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• 2019

4차산업혁명 시대의 도래로 빅데이터, AI 기술 등을 이용하여 데이터 수집, 분석, 가공, 활용에 관심이 높아졌다. 정부도 공공부문 정보시스템의 보유데이터를 개방하여 산업 전반에 데이터 연계·활용을제고하고 있다. 본 연구는 도로건설사업의 업무처리를 지원하는 건설사업정보시스템(CALS)에 보유중인 건설데이터를 개방하기 위한 방안을 마련하였다. 이를 위해 건설데이터 중 개방 가능한 데이터를 선정하고 키워드를 통한 데이터 및 파일의 정보검색 환경과 데이터 공개서비스 구축방법을 제시하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.149-152
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• 2024

본 논문에서는 자치구별 집 가격과 인프라 데이터를 통한 분석을 기반으로, 저렴한 주택 지역에 입주하는 사람들의 우려와 관련하여 좋은 동네와 안좋은 동네의 차이를 다각도로 조망하고자 한다. DataSet은 서울 열린 데이터 광장과 보건의료 빅데이터 개방 시스템에서 수집한 공공데이터를 활용한다. dependent variable로는 자치구별 인프라 데이터셋을 사용하였으며, independent variable는 자치구별 집 가격을 기반으로 데이터 분석을 수행한다. 본 논문에서는 다양한 분석 기법을 활용하여 모델의 정확도와 신뢰성을 향상시키고, 이를 토대로 동네의 특징과 주거 환경의 차이를 명확히 도출하여 결론을 이끌어내고자 한다.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.105-122
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• 2007

To understand the present status and the development of the digital reference service in Korean public libraries, a nationwide site observation was attempted in 2007. The collected data was analyzed, then compared with the previous analysis based on a 2003 data. For the 404 sites offering digital reference, operational characteristics, such as access level, service mode, link description, policy, web form, and FAQ, are analyzed, Performance analysis focused on the presence of question posting, volume of usage, response rate, and types of the questions, for the data collected for 15 days through question and answer transcript recording. Results reveal findings on the present situation as well as changes over 4 years. Related problems are identified. The conclusion includes suggestions for improving digital reference service.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.491-514
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• 2022

Public reforms based on New Public Management have made the public sector specialized, and accordingly the role of public administration has expanded as well as the demand on professional jobs has increased. On the other hand, with the rapid development of information and communication technology, the data produced by public sector organizations has also significantly increased. This environmental changes made data management and a data management job in the public sector critical. However, there have been very few studies of conceptualizations and systematic investigations on data management jobs. Moreover, specific definitions, types or qualifications of/for a data management job or a person who do this job are rarely reflected in relevant laws and regulations. Based on the systematic literature review, this study conceptualized professionalism, identified its multiple dimensions, and draw a conceptual research framework. Focusing on the professional control on personnel management which is one of the dimensions of professionalism, relevant laws, work guidelines and job descriptions included in job openings were analyzed with regard to a data management job in the public sector. The findings are as follows. First, an assigned role and responsibility associated with a data management job have vague boundaries. Second, work guidelines and manuals only focus on the post quality control stage rather than equally addressing all the eight stages of the data lifecycle. Third, neither a data management job in the public sector nor a person who take care of this job is not appropriately defined. Therefore, a role and responsibility of/for the job and a person in charge should be reflected in the relevant laws and guidelines in a tailored way. More importantly, job analyses and evaluations should be thoroughly conducted to enhance professionalism on data management jobs in the long term.

• The Journal of Information Technology and Database
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• v.2 no.2
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• pp.3-24
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• 1995

본 연구는 국가정보화의 총괄적인 정보개발계획을 수립하기 위하여 일명 정보개발지도를 이용하여 국가의 정보개발 현황을 분석하고 국가 정보화의 방향을 제시하고자 한다. 이는 현재 국내에 개발되어 서비스를 제공중인 정보, 사업의 지원자금으로 개발을 추진중에 있는 정보, 혹은 아직 미개발되었지만 공공정보로써 개발이 가능한 공공기관의 정보자원을 조사하고 세부분야별로 분류하여 하나의 평면에 나타냄으로써 국내 공공정보 개발의 방위를 파악하고자 한다. 또한 해외의 정보개발, 서비스들을 평면에 함께 제시함으로써 향후 공공데이터베이스의 개발 과제를 파악하기 위한 기반자료로 활용될 수 있으며, 정보개발지도에 따라 년차별 개발분야 및 개발 우선순위 등을 결정될 수 있으리라 예측된다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.39-46
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• 2021

When conducting social big data analysis for franchise stores, reviews of multiple branches of a franchise can be collected together, from which analysis results can be distorted significantly. To improve its accuracy, it should be possible to filter reviews of other branches properly which are not subject to the analysis. This paper presents a method for social big data analysis which reflects characteristics of franchise stores. The proposed method consists of search key configuration and review filtering. For the former, the open data provided by Small Business Promotion Agency is used to extract region names for collecting reviews more accurately. For the latter, open search APIs provided by Naver or Kakao are used to obtain franchise branch information for filtering reviews of other branches that are not subject to analysis. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that the accuracy of the proposed review filtering was 93.6% on the average.

• Journal of Korean Library and Information Science Society
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• v.50 no.3
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• pp.217-238
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• 2019

Recently, interest in Public Lending Right has increased in Korea. This study aims to collect valuable data necessary for the discussion of the introduction of Public Lending Right by analyzing the loan statistics of 820 public libraries nationwide for five years from 2014 to 2018. In order to analyze the loan statistics of Korean public libraries, 1,178,300,000 big data provided by 'Data for Library' operated by the National Library of Korea were used. Through the analysis of loan statistics, 125 books were identified, which have been lent the most in the last five years. The study examined the 125 books to find out who are authors and Japanese authors and authors' nationality. The study also analyzed publishers and number of lending of cartoons.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.1-23
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• 2021

The purpose of this study is to analyze the effects of the bestseller ranks on the book circulations in public libraries. To achieve this goal, the weekly data sets of 179 books' library circulation and bestseller list from January 1, 2018 to December 29, 2019 were constructed based on the data collected from BigData MarketC and YES24. Three methods for analyzing panel data including linear regression, fixed-effect, and random effect models were compared, and it turned out that fixed-effect model was better than other methods. The results show that the average ranks of bestsellers were associated with their public library circulations visually. Also, the analysis of fixed-effect model showed that the single rank decline of a book on the bestseller list decreases its average circulation of 0.108 while the size of effect varied depending on subject of books. The study empirically demonstrated the impact of a bestseller list on people's book circulation behavior, suggesting that public libraries need to reference sociocultural context as well as bestseller book lists to predict library user needs and to formulate collection development policy.