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RDF graph validation using rule-based reasoning

Ben De Meester (UGent) , Pieter Heyvaert (UGent) , Dörthe Arndt (UGent) , Anastasia Dimou (UGent) and Ruben Verborgh (UGent)
(2021) SEMANTIC WEB. 12(1). p.117-142
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Abstract
The correct functioning of Semantic Web applications requires that given RDF graphs adhere to an expected shape. This shape depends on the RDF graph and the application's supported entailments of that graph. During validation, RDF graphs are assessed against sets of constraints, and found violations help refining the RDF graphs. However, existing validation approaches cannot always explain the root causes of violations (inhibiting refinement), and cannot fully match the entailments supported during validation with those supported by the application. These approaches cannot accurately validate RDF graphs, or combine multiple systems, deteriorating the validator's performance. In this paper, we present an alternative validation approach using rule-based reasoning, capable of fully customizing the used inferencing steps. We compare to existing approaches, and present a formal ground and practical implementation "Validatrr", based on N3Logic and the EYE reasoner. Our approach - supporting an equivalent number of constraint types compared to the state of the art - better explains the root cause of the violations due to the reasoner's generated logical proof, and returns an accurate number of violations due to the customizable inferencing rule set. Performance evaluation shows that Validatrr is performant for smaller datasets, and scales linearly w.r.t. the RDF graph size. The detailed root cause explanations can guide future validation report description specifications, and the fine-grained level of configuration can be employed to support different constraint languages. This foundation allows further research into handling recursion, validating RDF graphs based on their generation description, and providing automatic refinement suggestions.
Keywords
LINKED DATA, OWL, Constraints, rule-based reasoning, validation

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Citation

Please use this url to cite or link to this publication:

MLA
De Meester, Ben, et al. “RDF Graph Validation Using Rule-Based Reasoning.” SEMANTIC WEB, vol. 12, no. 1, Ios Press, 2021, pp. 117–42, doi:10.3233/SW-200384.
APA
De Meester, B., Heyvaert, P., Arndt, D., Dimou, A., & Verborgh, R. (2021). RDF graph validation using rule-based reasoning. SEMANTIC WEB, 12(1), 117–142. https://doi.org/10.3233/SW-200384
Chicago author-date
De Meester, Ben, Pieter Heyvaert, Dörthe Arndt, Anastasia Dimou, and Ruben Verborgh. 2021. “RDF Graph Validation Using Rule-Based Reasoning.” SEMANTIC WEB 12 (1): 117–42. https://doi.org/10.3233/SW-200384.
Chicago author-date (all authors)
De Meester, Ben, Pieter Heyvaert, Dörthe Arndt, Anastasia Dimou, and Ruben Verborgh. 2021. “RDF Graph Validation Using Rule-Based Reasoning.” SEMANTIC WEB 12 (1): 117–142. doi:10.3233/SW-200384.
Vancouver
1.
De Meester B, Heyvaert P, Arndt D, Dimou A, Verborgh R. RDF graph validation using rule-based reasoning. SEMANTIC WEB. 2021;12(1):117–42.
IEEE
[1]
B. De Meester, P. Heyvaert, D. Arndt, A. Dimou, and R. Verborgh, “RDF graph validation using rule-based reasoning,” SEMANTIC WEB, vol. 12, no. 1, pp. 117–142, 2021.
@article{8684858,
  abstract     = {{The correct functioning of Semantic Web applications requires that given RDF graphs adhere to an expected shape. This shape depends on the RDF graph and the application's supported entailments of that graph. During validation, RDF graphs are assessed against sets of constraints, and found violations help refining the RDF graphs. However, existing validation approaches cannot always explain the root causes of violations (inhibiting refinement), and cannot fully match the entailments supported during validation with those supported by the application. These approaches cannot accurately validate RDF graphs, or combine multiple systems, deteriorating the validator's performance. In this paper, we present an alternative validation approach using rule-based reasoning, capable of fully customizing the used inferencing steps. We compare to existing approaches, and present a formal ground and practical implementation "Validatrr", based on N3Logic and the EYE reasoner. Our approach - supporting an equivalent number of constraint types compared to the state of the art - better explains the root cause of the violations due to the reasoner's generated logical proof, and returns an accurate number of violations due to the customizable inferencing rule set. Performance evaluation shows that Validatrr is performant for smaller datasets, and scales linearly w.r.t. the RDF graph size. The detailed root cause explanations can guide future validation report description specifications, and the fine-grained level of configuration can be employed to support different constraint languages. This foundation allows further research into handling recursion, validating RDF graphs based on their generation description, and providing automatic refinement suggestions.}},
  author       = {{De Meester, Ben and Heyvaert, Pieter and Arndt, Dörthe and Dimou, Anastasia and Verborgh, Ruben}},
  issn         = {{1570-0844}},
  journal      = {{SEMANTIC WEB}},
  keywords     = {{LINKED DATA,OWL,Constraints,rule-based reasoning,validation}},
  language     = {{eng}},
  location     = {{Nancy, FRANCE}},
  number       = {{1}},
  pages        = {{117--142}},
  publisher    = {{Ios Press}},
  title        = {{RDF graph validation using rule-based reasoning}},
  url          = {{http://dx.doi.org/10.3233/SW-200384}},
  volume       = {{12}},
  year         = {{2021}},
}

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