Libraly Journal

Libraly Journal ›› 2019, Vol. 38 ›› Issue (1): 65-73.

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Construction of Semantic Knowledge Model and Association Research for Bibliographic Data

Chen Tao, Zhang Yongjuan, Shan Rongrong, Li Xin, Liu Wei   

  • Online:2019-01-15 Published:2019-01-24

Abstract: With the rapid development of the Semantic Web and Linked Data technologies in the field of library and information, more and more organizations use the BIBFRAME framework to organize their bibliographic resources. Single volume, compilation work, series, and aggregation work are common forms of work in bibliographic data. In this paper, from the perspective of Linked Data and knowledge organization, we model different forms of works using the framework of BIBFRAME. In addition, this paper also proposes a knowledge correlation model of bibliographic data in the framework of BIBFRAME. We also guide the association and integration of bibliographic data with other open resources from multiple perspectives.

Key words: Bibliographic data, BIBFRAME, Knowledge modeling, Linked knowledge framework