• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.493-519
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• 2021

The purpose of this study is to propose a plan to implement the comprehensive linking system centered on identifiers in order to provide seamless academic information services to researchers. To achieve this goal, interviews were conducted with 17 researchers from five centers and one secretariat belonging to KISTI. The contents of the interview are about the establishment and management status of the identifier of the academic information service DB. As a result of the interview, it was found that the identification rate for identifiers such as KOI was high in the case of domestic articles DB, but the identification rate for global identifiers such as ORCID was low in the case of foreign articles DB except for DOI. To solve this problem, this study proposes the council for joint use of a comprehensive linking system to build the comprehensive linking system model centered on identifiers. The joint use council will be organized around domestic academic information distribution institutions, and the council is expected to discover and implement new services through ID linkage by collecting foreign identifiers.

• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.115-143
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• 2020

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.