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Intellectual Structure Analysis on the Field of Open Data Using Co-word Analysis (동시출현단어 분석을 이용한 오픈 데이터 분야의 지적 구조 분석)

  • HyeKyung Lee;Yong-Gu Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.429-450
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    • 2023
  • The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.

A Study on Ontology Based Knowledge Representation Method with the Alzheimer Disease Related Articles (알츠하이머 관련 논문을 대상으로 하는 온톨로지 기반 지식 표현 방법 연구)

  • Lee, Jaeho;Kim, Younhee;Shin, Hyunkyung;Song, Kibong
    • Journal of Internet Computing and Services
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    • v.15 no.3
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    • pp.125-135
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    • 2014
  • In the medical field, for the purpose of diagnosis and treatment of diseases, building knowledge base has received a lot of attention. The most important thing to build a knowledge base is representing the knowledge accurately. In this paper we suggest a knowledge representation method using Ontology technique with the datasets obtained from the domestic papers on Alzheimer disease that has received a lot of attention recently in the medical field. The suggested Ontology for Alzheimer disease defines all the possible classes: lexical information from journals such as 'author' and 'publisher' research subjects extracted from 'title', 'abstract', 'keywords', and 'results'. It also included various semantic relationships between classes through the Ontology properties. Inference can be supported since our Ontology adopts hierarchical tree structure for the classes and transitional characteristics of the properties. Therefore, semantic representation based query is allowed as well as simple keyword query, which enables inference based knowledge query using an Ontology query language 'SPARQL'.

A Study on the Metadata based on the Semantic Structure of the Korean Studies Research Articles (한국학 연구 논문의 의미 구조 기반 메타데이터 연구)

  • Song, Min-Sun;Ko, Young Man
    • Journal of Korean Library and Information Science Society
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    • v.46 no.3
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    • pp.277-299
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    • 2015
  • The purpose of this study is to build a metadata set based on the semantic structure of the Korean studies research articles. For this purpose, we analyzed the related researches which suggested the semantic structure of the research articles, categorized the concepts of author keywords of the Korean studies research articles, and drew the metadata set of 16 elements from the results of the analysis and the categorization. The significance of this study is that it propose a semantic metadata configuration methodology which can reflect the scholarly sense-making of researchers in Korean studies. Especially, this study is significant because it reflects the keywords which was given by the actual researchers to examine the content characteristics of the Korean studies research articles.

Analysis of 'Digital Divide' Research Trends in Library and Information Science (문헌정보학 분야 정보격차 연구동향 분석)

  • Kang, In-Seo;Kim, Hea-Jin
    • Journal of the Korean Society for information Management
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    • v.37 no.2
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    • pp.333-352
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    • 2020
  • This study aimed to analyze research trends of 'digital divide' in Library and Information Science. To this end, we coded research subjects with 11 subcategories, and research objectives with 4 subcategories, and research methods with 4 subcategories, and constructed keyword networks to which a pathfinder algorithm was applied. As a result of the analysis, 79.5% of studies are on the disabled, multicultural families, and the elderly among information vulnerable groups, and it was found to be concentrated in specific groups. In addition, digital divide related studies have been actively conducted for the purpose of resolving information vulnerabilities such as people with disabilities. We also found that these studies focused on verifying the effectiveness by designing and applying treatments such as informatization education, information utilization, and reading programs. Lastly, the most frequently used research method in the digital divide was found to use case studies or questionnaires simultaneously with literature research.

Patterns of Collaboration Networks:Co-authorship Analysis of MIS Quarterly from 1996 to 2004 (협력 네트워크 패턴에 관한 연구: MIS Quarterly 공저자 분석을 중심으로)

  • Huang, Ming-Hao;Ahn, Joong-Ho;Jahng, Jung-Joo
    • The Journal of Society for e-Business Studies
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    • v.13 no.4
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    • pp.193-207
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    • 2008
  • The study investigates the co-authorship networks of MIS Quarterly as one of the leading journals in IS field and examines patterns of collaboration networks of the intellectuals. These issues are addressed through a systematic Social Network Analysis (SNA) of 242 articles published from 1996 to 2004 in MIS Quarterly. Results of co-authorship network analysis indicate that the whole incomplete network has a low degree of density. Thus, we analyzed three biggest sub-networks to find out who the key players of each sub-network are. Then, following the keyword classification scheme, relevant data from the articles were collected and coded to analyze three major co-authorship networks of MIS Quarterly community. Some implications are drawn from different research keywords of each sub-network.

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Analysis of major research trends in artificial intelligence through analysis of thesis data (논문데이터 분석을 통한 인공지능 분야 주요 연구 동향 분석)

  • Chung, Myoung-Sug;Park, Seong-Hyeon;Chae, Byeong-Hoon;Lee, Joo-Yeoun
    • Journal of Digital Convergence
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    • v.15 no.5
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    • pp.225-233
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    • 2017
  • In this paper, we collected the articles related to artificial intelligence among SCI(E) journals published by Korean authors in 'Web of Science' and conducted frequency analysis and keyword network analysis. As a result of the analysis, the artificial intelligence thesis showed an average growth of about 10% per year, but the relative ratio decreased. As time went on, we could confirm that there is a lot of practical and applied research in artificial intelligence research. Unlike the US 'National Strategy for Artificial Intelligence Research and Development,' the field of research in Korea was focused on local and technical aspects. Therefore, Korea should go beyond the theoretical and technical iterations of artificial intelligence, and research should be carried out to present a comprehensive future direction.

Analysis of Research Subject Network in the Field of Oncogene (암유전자 연구주제 네트워크 분석)

  • Jang, Hae-Lan;Kang, Gil-Won;Lee, Eun-Jung;Kim, Seung-Ryul;Lee, Young-Sung
    • Journal of Korea Technology Innovation Society
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    • v.15 no.2
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    • pp.369-399
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    • 2012
  • Purpose: Health technology research & development is an important area to leading future. This study examined the current trends for 'oncogene' based on the research subject network to deduce a research front. Method: Papers were extracted from PubMed database using MeSH term for studies on 'oncogenes' and further categorized as papers published by Korean. Keywords were collected from all of articles. Research subject network was generated by keywords. Research subject network was analyzed by weighted degree centrality based social network analysis and transition of research subjects was analyzed by the time series. Results: On 'oncogenes', 'Genes, ras', 'Apoptosis', 'Signal Transduction' had a high degree centrality and currently 'Antineoplastic Agents', 'Prognosis', and 'Tumor Markers, Biological' were widely conducted. Conclusion: Consistency of research trend pattern was found by analyzing oncogene network with compromised to international vs. domestic trends. Analyzing keyword networks in various subject area, those will allow us to predict the research progress and propose evidence of research & developmental strategy.

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An Analysis on the Trends and Issues of Convergence Technology Research (네트워크 분석을 통한 국내 융합기술 연구동향 분석)

  • Lim, Jung-Yeon
    • Journal of Internet of Things and Convergence
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    • v.4 no.1
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    • pp.23-29
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    • 2018
  • The purpose of study was to analyze the trends of 2005 to 2018 revised 'convergence technology research' through text network analysis using NetMiner4.0 program. Data analysis was conducted by using keyword analysis, centrality analysis of 653 authors' keyword from 177 journals. The results of the study are as follows. First, Research on Converging Technology has been studied steadily over the past 13 years in Department of Industry Convergence. Second, the results of the search term frequency analysis show that the 'convergence technology', 'technology convergence', 'convergence', 'design', 'convergence education', 'STEAM', 'convergence research' were used as the main keywords of convergence technology research. Third, Community analysis results show that five communities have been classified five categories according to the characteristics of the search terms 'only IT', 'Cultural industry utilizing Convergence contents', 'Technology innovation and research analysis' And patent development'. Based on these results, we proposed the future directions of convergence technology research.

Comparative Analysis of Research Trends in Reading Ability-related Fields (독서 능력과 읽기 능력의 연구 동향 비교 분석)

  • Sena Lee
    • Journal of Korean Library and Information Science Society
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    • v.54 no.3
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    • pp.223-248
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    • 2023
  • This study was conducted to compare and analyze trends in research on reading ability. To do this, collecting articles searched for 'reading ability', a keyword network analysis was performed based on the author's keyword. As a result of the analysis, it was found that the terms were used interchangeably in studies related to reading education at universities. In the study related to reading ability 1, the main research areas are school library, school librarian, information literacy, self-directed learning, and information service. In the study related to reading ability 2, the main research areas are children's early literacy, related reading difficulty and disability. In addition, studies on reading evaluation are being conducted in both areas, but not much activation has been performed. Studies involving adolescents show limited activity in both areas.

A Comparative Analysis of Research Trends in Korean Modern Medicine: Focusing on Two Journals of Medical School (근대의학 논문의 계량학적 방법을 통한 연구 경향 비교 분석 - 의학전문학교 학술지 2종을 중심으로 -)

  • Mijin Seo;Jisu Lee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.34 no.4
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    • pp.29-54
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    • 2023
  • This study aimed to analyze the research trends of journal articles published by medical schools representing Korean modern. A total of 682 were selected from two journals published by Medical College in Keijo and Keijo Imperial University Medical Faculty. In results, the affiliations of authors who participated in Acta Medicinalia in Keijo included various schools and hospitals, and the authors' major was found to be similar in basic medicine and clinical medicine. In The Keijo Journal of Medicine, only school-affiliated authors participated, and 96.33% of the authors were majors in basic medicine. Co-occurrence network analysis was conducted on MeSH terms from the title of the article using MeSH on Demand, and the keyword that derived in both journals was 'erythrocytes', which analyzed the condition of red blood cells according to organs and diseases. In frequency analysis, a common area of research in both journals was the study focusing on blood and blood cells, and the study of anemia and tuberculosis, which were prevalent diseases at the time. As for comparing each journal, Acta Medicinalia in Keijo has focused on inflammatory diseases and clinical pathological studies in humans, and The Keijo Journal of Medicine has focused on anatomical studies on animals and pharmacological studies on medicines. Through this study, it was possible to identify the research topics and major keywords in two medical schools with different founding goals.