农业图书情报 ›› 2019, Vol. 31 ›› Issue (3): 13-24.doi: 10.13998/j.cnki.issn1002-1248.2019.03.19-0367

• 特约综述 • 上一篇    下一篇

关联数据研究的主题结构和研究进展解析

周毅, 刘峥, 张建勇   

  1. 中国科学院文献情报中心,北京 100190
  • 收稿日期:2019-01-30 出版日期:2019-03-05 发布日期:2019-06-04
  • 作者简介:周毅(ORCID: 0000-0002-1494-6716),硕士,馆员。刘峥(ORCID: 0000-0002-2494-436X),博士,副研究馆员,Email: liuz@mail.las.ac.cn。张建勇(ORCID:0000-0001-7533-1726),硕士,研究馆员。
  • 基金资助:
    国家科技图书文献中心(NSTL)资助项目“名称规范数据库建设”子任务“名称规范数据库的语义表示”

Research on Subject Structure and Research Progress of Linked Data

ZHOU Yi, LIU Zheng, ZHANG Jianyong   

  1. National Science Library, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2019-01-30 Online:2019-03-05 Published:2019-06-04

摘要: [目的/意义]通过调研关联数据的研究文献,分析关联数据的研究的主题结构与研究进展。[方法/过程] 综合采用文献综述方法、文献计量方法与可视化工具对Web of Science中的关联数据研究进行分析。其中,利用Citespace可视化软件分析了关联数据研究主体,利用VOSviewer将构建的关键词矩阵可视化。以关联数据的生命周期阶段为线索,结合关键词共现图谱,探寻了关联数据研究的主题结构与研究进展。[结果/结论]分析结果显示欧洲为关联数据研究的主阵地,Tim Berners-Lee等人在关联数据领域具备深厚的影响力。目前关联数据的研究覆盖了发布、优化、评价、应用等生命周期各个方面,但也存在一些薄弱环节,如在研究推动关联数据发布的进一步规范、实现实体自动丰富与链接、构建全面的质量评价体系与工具等方面存在挑战。

关键词: 关联数据, 主题结构, 研究进展, 计量分析

Abstract: [Purpose/Significance] This paper is intend to find out the subjects structure and research progress in the field of linked data by investigating the relevant research literature.[Method/Process] Several research methods were used to analyze the linked data research in Web of Science, such as bibliometric method and visualization method. We used Citespace as visualization tool to find out who is researching on linked data. Based on the life cycle of linked data, the subject structure and research progress of linked data are explored.[Result/Conclusion] The results show that Europe is the main area for linked data researching, and Tim Berners-Lee et al. have a deep influence in the field. At present, the research of linked data covers all aspects of its life cycle include generate and publish, optimization, evaluation and application. Meanwhile there are also some weak points, such as further research on promoting the publish of linked data with high quality, realizing automatic enrichment and linking of entities, and constructing comprehensive quality evaluation.

中图分类号: 

  • G202

引用本文

周毅, 刘峥, 张建勇. 关联数据研究的主题结构和研究进展解析[J]. 农业图书情报, 2019, 31(3): 13-24.

ZHOU Yi, LIU Zheng, ZHANG Jianyong. Research on Subject Structure and Research Progress of Linked Data[J]. Agricultural Library and Information, 2019, 31(3): 13-24.