Publishing E-RDF linked data for many agents by single third-party server

Dongsheng Wang, Yongyuan Zhang, Zhengjun Wang, Tao Chen

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


Linked data is one of the most successful practices in semantic web, which has led to the opening and interlinking of data. Though many agents (mostly academic organizations and government) have published a large amount of linked data, numerous agents such as private companies and industries either do not have the ability or do not want to make an additional effort to publish linked data. Thus, for agents who are willing to open part of their data but do not want to make an effort, the task can be undertaken by a professional third-party server (together with professional experts) that publishes linked data for these agents. Consequently, when a single third-party server is on behalf of multiple agents, it is also responsible to organize these multiple-source URIs (data) in a systematic way to make them referable, satisfying the 4-star data principles, as well as protect the confidential data of these agents. In this paper, we propose a framework to leverage these challenges and design a URI standard based on our proposed E-RDF, which extends and optimizes the existing 5-star linked data principles. Also, we introduce a customized data filtering mechanism to protect the confidential data. For validation, we implement a prototype system as a third-party server that publishes linked data for a number of agents. It demonstrates well-organized 5-star linked data plus E-RDF and shows the additional advantages of data integration and interlinking among agents.

Original languageEnglish
Title of host publicationSemantic Technology - 7th Joint International Conference, JIST 2017, Proceedings
Number of pages13
Volume10675 LNCS
ISBN (Print)9783319706818
Publication statusPublished - 2017
Event7th Joint International Conference on Semantic Technology, JIST 2017 - Gold Coast, Australia
Duration: 2017 Nov 102017 Nov 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10675 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th Joint International Conference on Semantic Technology, JIST 2017
CityGold Coast

Subject classification (UKÄ)

  • Information Systems

Free keywords

  • Data integration
  • E-RDF
  • Knowledge representation
  • Linked data
  • Semantic web
  • Web service


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