RDF Graph Validation Using Rule-Based Reasoning

Tracking #: 1998-3211

This paper is currently under review
Ben De Meester
Pieter Heyvaert
Dörthe Arndt1
Anastasia Dimou
Ruben Verborgh

Responsible editor: 
Axel Polleres

Submission type: 
Full Paper
Semantic Web applications cannot function when the given data – i.e., an RDF graph – is not interpreted as expected. RDF graphs can be validated by defining and assessing constraints. These constraints define an RDF graph that can be correctly interpreted for a specific Semantic Web application or use case. Which entailment regime is used – e.g., whether rdfs:subClassOf inferencing is taken into account or not – is an integral part of how the RDF graph should be interpreted, and thus of the proper functioning of the application. Different types of validation approaches are proposed to assess these constraints, namely hardcoded systems, ontology reasoners, and querying endpoints. However, these approaches do not allow to fully customize which inferencing is supported to match the entailment regimes as intended by the use case. They are thus unable to validate RDF graphs properly or need to combine systems, deteriorating the performance of the validation. In this paper, we present an alternative validation approach using rule-based reasoning, capable of fully customizing the inferencing rules during validation. We compare existing approaches with a rule-based reasoning approach, and present both a formal ground and practical implementation based on N3Logic and the EYE reasoner. Our approach (a) better explains the root cause of the violations due to the formal logical proof of the reasoner, (b) returns an accurate number of violations due to explicit inferencing rules, and (c) supports more constraint types by including inferencing up to at least OWL-RL complexity and expressiveness. Moreover, our performance evaluation shows that our implementation is faster than combining existing approaches. By allowing to precisely define the inferencing rules together with the constraints, we provide a more complete validation approach. We ensure validated RDF graphs can be interpreted as intended with additional inferencing, allowing more precise Semantic Web applications, and opening opportunities for automatic RDF graph refinement and validating implicit graphs based on their generation rules.
Under Review