• Title/Summary/Keyword: National R&D Reference Information Ontology

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A Design and Implementation of National R&D Reference Information Ontology Based on URI Server (URI 서버에 기반한 국가 R&D 기반정보 온톨로지 설계 및 구현)

  • Jung, Han-Min;Kang, In-Su;Koo, Hee-Kwan;Lee, Seung-Woo;Sung, Won-Kyung
    • Journal of Information Management
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    • v.37 no.2
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    • pp.109-136
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    • 2006
  • The development of Semantic Web basically requires knowledge which is induced by the formalization and semantization of information, and thus ontology should be introduced as a knowledgization tool. URI(Uniform Resource Identifier) is an indispensible scheme to uniquely indicate individuals on ontology. However, it is difficult to find the use cases of identifiers or URIs in real data sets including science & technology publications. This paper describes the method to construct, manage, and serve reference information based on URI which is a crucial component on establishing national R&D reference information ontology. We expect the reference information which was acquired from about 7,000 proceeding papers would be adopted to Semantic Web applications such as researcher network analysis and outcome statistics.

An Implementation of URI Management and Service System for the Construction of National R&D Reference Information Ontology (국가 과학기술 R&D 기반정보 온톨로지 구축을 위한 URI 관리 및 서비스 시스템 구현)

  • Koo Hee-Kwan;Jung Han-Min;Kang In-Su;Sung Won-Kyung;Yi Seung-June;Shim Bin-Gu
    • Proceedings of the Korean Information Science Society Conference
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    • pp.217-219
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    • 2006
  • 전체적인 관점으로 국가 과학기술 R&D를 조망하는 국가 과학기술 R&D 기반정보 온톨로지는 인력정보, 과제정보, 성과정보를 포함하며 여러 URI들과 연계된다. 본 논문에서는 기존의 단일 URI 체계가 아닌 시스템 적이고 다층적인 국가 과락기술 R&D 기반정보 온톨로지의 인스턴스 레벨에 필요한 다중 URI 관리 및 서비스 시스템을 구현한다. 본 시스템은 관리적인 측면에서 웹 인터페이스 기반 URI 등록과 조회를, 서비스 측면에서 URI 질의중심의 웹서비스를 제공한다. 기존 정보(KISTI의 KOI, 학술진흥재단의 부서 및 기관, 국가과학기술인력 종합정보시스템의 인력DB)와 연계를 기반으로 가용성 및 재사용성을 높이고 신규정보를 위한 URI 생성규칙을 제공함으로써 URI 관리 및 서비스 시스템 완성도를 높였다.

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Construction of Researcher Network in the Academic Research Area based on Inference (학술 연구 분야에서의 추론 기반 연구자네트워크 생성)

  • Lee, Seung-Woo;Kim, Pyung;Jung, Han-Min;Koo, Hee-Kwan;Sung, Won-Kyung
    • Proceedings of the Korea Contents Association Conference
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    • pp.90-94
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    • 2006
  • The research about social network for analyzing human relationship has been steadily worked due to the importance in the social science field. It is also important that analyzing the relationship between researchers in the academic and research fields. Especially, the network by joint research or citation between researchers is useful to evaluating projects or making policy on academic and research fields. This paper describes a method that generates two kinds of researcher networks showing co-authorship and citation relationship between researchers based on national R&D reference information ontology. We infer pair of researchers in co-authorship or citation relationship by SPARQL query from the ontology which is composed of research outcomes and their participating researchers in RDF triples. By postprocessing, we construct researcher network which links researchers in co-authorship and citation relationship.

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Construction of Human Resources from Science & Technology Publications for Supporting of Ontology Construction (온톨로지 구축 지원을 위한 과학기술 문헌으로부터의 인력정보 구축)

  • Jung, Han-Min;Lee, Seung-Woo;Kang, In-Su;Sung, Won-Kyung
    • Proceedings of the Korea Contents Association Conference
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    • pp.223-226
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    • 2006
  • The development of Semantic Web basically requires knowledge induced from the formalization and semantization of information, and thus ontology should be introduced as a knowledgization tool. URI(Universal Resource Identifier) is an indispensible scheme to uniquely indicate individuals on ontology. However, it is difficult to find the use cases of URI in real data including science & technology publications. This paper describes the method to construct human resources based on URI which are the critical components on national R&D reference information ontology. We use co-authors, e-mails, publication date, and affiliation for discriminating authors with the same strings. HRST is referred to acquire human resource URIs. We expect the human resources would be adopted to outcome analysis applications such as researcher network analysis and outcome statistics.

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