Journal of Korean Library and Information Science Society (한국도서관정보학회지)

Korean Library and Information Science Society (한국도서관정보학회)
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A Study on the Analysis of Identification System and the Linkage Method of Academic-information

학술정보의 식별체계 현황 분석 및 연계 방안 연구

  • 강주연 (한국과학기술정보연구원 콘텐츠큐레이션센터) ;
  • 설재욱 (한국과학기술정보연구원 콘텐츠큐레이션센터) ;
  • 황혜경 (한국과학기술정보연구원 콘텐츠큐레이션센터)
  • Received : 2020.02.20
  • Accepted : 2020.03.14
  • Published : 2020.03.31
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Abstract

With the era of the 4th Industrial Revolution, the number of data-centric integrated researches increases. The integrated researches make information identification and linkage more important, so it is necessary to seek a method to efficiently manage and share academic-information for supporting the researches. Therefore, this study aims to analyze identification system and linkable information types of 12 major academic search engines and bibliographic databases(ASEBDs) in Korea and abroad and to propose a method to identify and link academic-information. The analysis was conducted 2 times, and academic-information types, searchable fields, linkable information types, used identification system were investigated. As a result, the ASEBDs link directly or/and indirectly 3~4 information types based on their own identifiers with persistent identifiers. In addition, they identify academic-information semi-automatically based on machine learning methodology and collect and manage the related data. Finally, the method for academic-information linkage was proposed in terms of practice and society: linkage based on persistent identifiers and linkage based on collaborative network of institutions.

4차 산업혁명 시대의 도래로 데이터 중심의 융합 연구가 증가하고 있다. 이러한 연구는 정보의 식별 및 연계의 중요성을 증가시키고 있어, 이를 지원하기 위한 학술정보의 효과적인 관리 및 유통을 위한 방안 모색이 필요하다. 이에 본 연구는 국내외 주요 학술정보서비스 12개의 식별체계 현황과 연계 가능한 정보를 분석하여 학술정보를 식별하고 연계할 수 있는 방안을 제안하고자 하였다. 현황 분석은 2차에 걸쳐 진행되었으며, 각 서비스가 제공하고 있는 학술정보의 유형과 검색 가능한 항목, 연계 정보 유형, 사용 중인 식별체계 등을 살펴보았다. 분석 결과, 국내외 주요 학술정보서비스들은 영구 식별자와 더불어 자체 식별자를 중심으로 평균 3~4개의 정보를 직·간접적으로 연계하고 있다. 또한, 기계학습 방법론을 기반으로 하여 동일 학술정보를 반자동으로 식별하고, 해당 데이터를 수집, 구축하고 있다. 상기 분석 결과를 바탕으로 실무적인 측면에서 영구 식별자 중심의 학술정보 연계 방안과 사회적인 측면에서 기관 협력 네트워크 기반의 연계 방안을 제안하였다.

Keywords

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