• Title/Summary/Keyword: 데이터 인용

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The Current State and Recommendations for Data Citation (데이터 인용의 현황과 제언)

  • Kim, Jihyun;Chung, EunKyung;Yoon, JungWon;Lee, Jae Yun
    • Journal of the Korean Society for information Management
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    • v.34 no.1
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    • pp.7-29
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    • 2017
  • Data citation remains in its infancy, although providing the citation to a journal article is a typical norm in an academic community. This study examines the need for data citation, its principles and guidelines for improving the issue. In addition, the study investigates cases that established data citation mechanism, including DataCite, Dataverse Network and Data Citation Index that define elements of data citation and provide relevant services. At the end, it explores the current state of data citation in Korea through the analysis of citations to dataset from Korean General Social Survey.

Development of Science Technology Information Service using Citation Information Data (인용정보 데이터를 활용한 과학기술 학술정보서비스 개발)

  • Park, Yoo-Na;Bae, Su-Yeong;Lee, Hye-Jin;Lee, Seok-Hyoung;Choi, Hee-Seok
    • The Journal of the Korea Contents Association
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    • v.20 no.12
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    • pp.241-249
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    • 2020
  • The citation information of academic resources contains the knowledge flow from previous research, so it is possible to connect fragmented research in relational aspects. The citation information can grasp the overall flow of research, so it can promote convergence research such as developing existing research or deriving related fields. Therefore, in this study, the citation information of academic literature, which was previously provided at the level of simple disclosure, was reconstructed based on the citation relationship. Through this, backward and forward citation analysis were conducted based on time series, and the research flow was analyzed by setting the citation stage. Finally, we developed an academic information service that visualizes the main research contents of backward and forward citation based on time series. This accesses academic resources through the meaning contained in the citation information.

Study about Research Data Citation Based on DCI (Data Citation Index) (Data Citation Index를 기반으로 한 연구데이터 인용에 관한 연구)

  • Cho, Jane
    • Journal of the Korean Society for Library and Information Science
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    • v.50 no.1
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    • pp.189-207
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    • 2016
  • Sharing and reutilizing of research data could not only enhance efficiency and transparency of research process, but also create new science through data integrating and reinterpretationing. Diverse policies about research data sharing and reutilizing have been developing, along with extending of research evaluating spectrum that across research data citation rate to social impact of research output. This study analyzed the scale and citation number of research data which has not been analyzed before in korea through data citation index using Kruskal-Wallis H analysis. As result, genetics and biotechnology are identified as subject areas which have most huge number of research data, however the subject areas that have been highly cited are identified as economics and social study such as, demographic and employment. And Uk Data Archive, Inter-university Consortium for Political and Social Research are analyzed as data repositories which have most highly cited research data. And the data study which describes methodology of data survey, type and so on shows high citation rate than other data type. In the result of altmetrics of research data, data study of social science shows relatively high impact than other areas.

A Study on Publication and Citation of Research Data (연구 데이터의 출판과 인용에 관한 연구)

  • Lee, sang-ho
    • Proceedings of the Korea Contents Association Conference
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    • 2017.05a
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    • pp.65-66
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    • 2017
  • 최근 오픈 사이언스 운동과 함께 정부 부처, 연구비 지원기관 등에서는 공적 기금으로 연구를 수행하는 경우 생성된 각종 연구 데이터를 관리하고 공개하도록 의무화하려는 움직임이 있다. 데이터에 DOI와 같은 식별자를 부여하여 데이터 리파지토리를 통해 출판하면 이해당사자들에게 많은 이익을 가져다 줄 수 있으며, 데이터의 인용을 활성화하기 위해 주제별 또는 기관별 리파지토리나 데이터센터에서 표준적인 인용 방법과 인용 요소들을 발표하고 있다. 앞으로 과학연구의 공개, 개방화가 더욱 추진되면 더욱 많은 연구데이터의 공유 활동이 일어날 것으로 예상되며 분야별 또는 유형별로 국제적인 데이터 리파지토리들이 출현하여 학술 논문의 근거가 되는 데이터 저장소로서의 역할을 수행할 것으로 생각된다.

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Objectivity in Korean News Reporting : Machine Learning-Based Verification of News Headline Accuracy (기계학습 기반 국내 뉴스 헤드라인의 정확성 검증 연구)

  • Baik, Jisoo;Lee, Seung Eon;Han, Jiyoung;Cha, Meeyoung
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.281-286
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    • 2021
  • 뉴스 헤드라인에 제3자의 발언을 직접 인용해 전언하는 이른바 '따옴표 저널리즘'이 언론 보도의 객관주의 원칙을 해치는지는 언론학 및 뉴스 구독자에게 중요한 문제이다. 이 연구는 온라인 포털사이트를 통해 실시간 유통되는 한국어 기사의 정확성을 판별하기 위한 기계학습(Machine Learning) 모델을 제안한다. 이 연구에서 제안하는 모델은 Edit Distance와 FastText 기법을 활용해 기사 제목과 본문 내 인용구의 유사성을 측정하고, XGBoost 모델을 활용해 최종 분류한다. 아울러 이 모델을 통해 229만 건의 뉴스 헤드라인에 대해 직접 인용구가 포함된 기사가 취재원의 발언을 주관적인 윤색없이 독자들에게 전하고 있는지를 판별했다. 이뿐만 아니라 딥러닝 기반의 KoELECTRA 모델을 활용해 기사의 제목 내 인용구에 대한 감성 분석을 진행했다. 분석 결과, 윤색이 가미되지 않은 직접 인용형 기사의 비율이 지난 20년 동안 10% 이상 증가했으며, 기사 제목의 인용구에 나타나는 감정은 부정 감성이 긍정 감성의 2.8배 정도로 우세했다. 이러한 시도는 앞으로 계산사회과학 방법론과 빅데이터에 기반한 언론 보도의 평가 및 개선에 도움을 주리라 기대한다.

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A study on method of citation information generation in Korean Patent Systems by using linking of core information resources (핵심정보자원 연계를 통한 국내 특허 인용 정보 생성 방법에 관한 연구)

  • 권오진;노경란;서진이;정의섭;유재영
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2005.10a
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    • pp.689-701
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    • 2005
  • 최근 특허청의 특허정보 활용 확산 정책으로 인하여 특허정보에 대한 관심이 집중되고 있다. 또한 특허정보를 연구하는 분야에서도 기술혁신 추세 분석, 기술혁신과 기술개발 주체에 대한 관계 분석을 수행하는 특허정보, 전산과학, 문헌정보학을 융합하는 특허정보학 (patinformatics)이라는 분야가 등장하였다. 특허정보를 이용한 최근의 연구동향은 특허 인용정보를 이용하여, 기술 파급효과 분석, 특허 인용지수, 기술영향력 지수, 특허가치 평가등 대부분의 연구가 인용정보를 기반으로 진행퇴고 있다. 기존의 연구 및 분석에 사용된 데이터는 미국특허의 인용정보를 이용하여 수행되고 있다. 한국특허 정보에는 인용정보가 존재하지 않기 때문이다. 한국특허의 분석을 위해서는 미국에 출원된 미국특허 데이터를 수집하여 한국의 연구개발 동향을 분석해야하는 문제점을 내포하고 있다 본 연구는 한국특허청 심사관의 인용정보 생성에 관한 업무 부하를 최소화하는 것을 목적으로 미국특허의 비 특허 문헌정보가 가지고 있는 문제점을 살펴봄으로써 국내에 구축되어 있는 과학기술문헌의 연계를 통한 효과적인 특허인용정보생성 방안을 제시하고자 한다.

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An Investigation on Characteristics and Intellectual Structure of Sociology by Analyzing Cited Data (사회학 분야의 연구데이터 특성과 지적구조 규명에 관한 연구)

  • Choi, Hyung Wook;Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.34 no.3
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    • pp.109-124
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    • 2017
  • Through a wide variety of disciplines, practices on data access and re-use have been increased recently. In fact, there has been an emerging phenomenon that researchers tend to use the data sets produced by other researchers and give scholarly credit as citation. With respect to this practice, in 2012, Thomson Reuters launched Data Citation Index (DCI). With the DCI, citation to research data published by researchers are collected and analyzed in a similar way for citation to journal articles. The purpose of this study is to identify the characteristics and intellectual structure of sociology field based on research data, which is one of actively data-citing fields. To accomplish this purpose, two data sets were collected and analyzed. First, from DCI, a total of 8,365 data were collected in the field of sociology. Second, a total of 12,132 data were collected from Web of Science with a topic search with 'Sociology'. As a result of the co-word analysis of author provided-keywords for both data sets, the intellectual structure of research data-based sociology was composed of two areas and 15 clusters and that of article-based sociology was composed with three areas and 17 clusters. More importantly, medical science area was found to be actively studied in research data-based sociology and public health and psychology are identified to be central areas from data citation.

An Investigation of Intellectual Structure on Data Papers Published in Data Journals in Web of Science (Web of Science 데이터학술지 게재 데이터논문의 지적구조 규명)

  • Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.37 no.1
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    • pp.153-177
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    • 2020
  • In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.

The Development of Citation Indicators of Korean Medical Journals (한국 의학학술지 인용지표 개발 연구)

  • 이춘실
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.13 no.1
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    • pp.27-41
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    • 2002
  • The study investigated the citation indicators and the citation analysis data developed in the KoMCI(Korean Medical Citation Index) project. With the full understanding of the current level of citation rates of Korean medical journals by Korean medical journals. and of the characteristics and problems associated with the KoMCI citation indicators, it is possible to further develop or modify citation indicators which will better represent the citation patterns of Korean medical journals. The highest impact factor reported in the KoMCI 2000 : Korean Medical Journal Citation Reports, which covered 69 Korean medical journals published in 2000 is 0.424 and the average is 0.182. It is because only 8.5% of references cited in Korean medical journal articles is to the Korean journal articles, The journal self-citation rates are very high (usually higher than 50%) due to the fact that there are only a few Korean journals published in the same subject area. The KoMCI impact factors of two Korean SCI journals for which SCI JCR reported the SCI 2000 impact factors are about 1/3 of the SCI impact factors. It is because SCI is based on the citations received from 5,900 journals whereas KoMCI is from 69 journals.

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A Study on the Description of Data Elements for the Citation Index of Academic Journals in Korea: with Special Reference to the Journal of the Korean Society for Information Management (국내 학술지 인용색인을 위한 데이터요소의 기술형태 분석: 정보관리학회지를 중심으로)

  • 김태수;남영광;최석두
    • Journal of the Korean Society for information Management
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    • v.16 no.2
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    • pp.183-199
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    • 1999
  • The three key parts of citation index are the Citation Index, the Source Index and the Permuterm Subject Index. To identify the core elements for citation index database system, it analyzed the items that have been cited in references and source items of Journal of the Korean Society for Information Management from vol. 1 no. l(1984) to vol. 15 no. 3(1998). Ten core elements were identified and the description format was specified respectively. The core elements are author, organization that the author is affiliated, title of article, title or journal, volume/numberlpage numbers, year of publication, keyword, language, subject category, statistics of references in article. Also, characteristics of errors in reference citations were analyzed and categorized in the viewpoint of the citation index development of academic journals in Korea.

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