Revealing the Conceptual Schemas of RDF Datasets

  • Subhi IssaEmail author
  • Pierre-Henri Paris
  • Fayçal Hamdi
  • Samira Si-Said Cherfi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11483)


RDF-based datasets, thanks to their semantic richness, variety and fine granularity, are increasingly used by both researchers and business communities. However, these datasets suffer a lack of completeness as the content evolves continuously and data contributors are loosely constrained by the vocabularies and schemes related to the data sources. Conceptual schemas have long been recognized as a key mechanism for understanding and dealing with complex real-world systems. In the context of the Web of Data and user-generated content, the conceptual schema is implicit. In fact, each data contributor has an implicit personal model that is not known by the other contributors. Consequently, revealing a meaningful conceptual schema is a challenging task that should take into account the data and the intended usage. In this paper, we propose a completeness-based approach for revealing conceptual schemas of RDF data. We combine quality evaluation and data mining approaches to find a conceptual schema for a dataset, this model meets user expectations regarding data completeness constraints. To achieve that, we propose LOD-CM; a web-based completeness demonstrator for linked datasets.


Conceptual modeling Completeness Model quality Conceptual schema mining Schema mining 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Subhi Issa
    • 1
    Email author
  • Pierre-Henri Paris
    • 1
  • Fayçal Hamdi
    • 1
  • Samira Si-Said Cherfi
    • 1
  1. 1.CEDRIC - Conservatoire National des Arts et MétiersParisFrance

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