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Kleenks: Collaborative Links in the Web of Data

Abstract : Linked Data is an initiative towards publishing and connecting structured data on the Web, creating what is called the Web of Data. This allows the creation of new types of applications, such as mash-ups and semantic searches, which make use of and integrate data coming from multiple online repositories. However, the large amount of content produced by blogs, wikis and social networks, which have become de facto standards for publishing content in Web 2.0, suggests that the growth of Web of Data could also be supported by adding a social, unstructured, collaborative dimension to it. In this paper we introduce "kleenks", which are collaborative links that combine structured and unstructured data by allowing users to add unstructured content to links, in addition to the RDF predicate. The quality and importance of such links can be evaluated by the community through classical mechanisms such as ratings and comments. This approach stimulates the emergence of more complex and abstract relations between entities, allowing people to take part in the Linked Data process and actively contribute to the growth of the Web of Data. We discuss how kleenks can be modeled on top of RDF and RDFS, making them easy to implement, and identify the main challenges to be addressed by a platform implementing the kleenks model. Finally, we introduce an online platform that successfully applies kleenks in the research domain by allowing researchers to create kleenks between articles, books and any other type of online media.
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Conference papers
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Contributor : Razvan Dinu <>
Submitted on : Thursday, October 4, 2012 - 5:13:51 PM
Last modification on : Thursday, May 24, 2018 - 3:59:23 PM


  • HAL Id : lirmm-00738652, version 1



Razvan Dinu, Ismail Andrei-Adnan, Tiberiu Stratulat, Jacques Ferber. Kleenks: Collaborative Links in the Web of Data. AI4KM'12: 1st International Workshop on Artificial Intelligence for Knowledge Management, Montpellier, France. pp.N/A. ⟨lirmm-00738652⟩



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