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

Wang, Dongsheng; Zhang, Yongyuan; Wang, Zhengjun LU and Chen, Tao (2017) 7th Joint International Conference on Semantic Technology, JIST 2017 In Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings 10675 LNCS. p.151-163
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Data integration, E-RDF, Knowledge representation, Linked data, Semantic web, Web service
in
Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings
volume
10675 LNCS
pages
13 pages
publisher
Springer Verlag
conference name
7th Joint International Conference on Semantic Technology, JIST 2017
external identifiers
  • scopus:85033791249
ISSN
0302-9743
1611-3349
ISBN
9783319706818
DOI
10.1007/978-3-319-70682-5_10
language
English
LU publication?
yes
id
c700999f-b1fc-4274-87bd-c75b29401789
date added to LUP
2017-11-29 13:12:12
date last changed
2018-01-07 12:27:06
@inproceedings{c700999f-b1fc-4274-87bd-c75b29401789,
  abstract     = {<p>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.</p>},
  author       = {Wang, Dongsheng and Zhang, Yongyuan and Wang, Zhengjun and Chen, Tao},
  booktitle    = {Semantic Technology - 7th Joint International Conference, JIST 2017, Proceedings},
  isbn         = {9783319706818},
  issn         = {0302-9743},
  keyword      = {Data integration,E-RDF,Knowledge representation,Linked data,Semantic web,Web service},
  language     = {eng},
  pages        = {151--163},
  publisher    = {Springer Verlag},
  title        = {Publishing E-RDF linked data for many agents by single third-party server},
  url          = {http://dx.doi.org/10.1007/978-3-319-70682-5_10},
  volume       = {10675 LNCS},
  year         = {2017},
}