Inference rules for OWL-P in N3Logic

Tomaszuk, Dominik

doi:10.15439/2018f102

Cited by 2 publications

(1 citation statement)

References 19 publications

(17 reference statements)

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“…We use N3Logic as it fulfills all requirements: SWRL does not support the logical requirement SNAF 9 , and the Datalog+/-framework does not support production of logical proofs. N3Logic is being actively supported and used, as evidenced by recent papers and patents [40,106,128,134], and by the recently founded W3C Notation 3 (N3) Community Group fostering development, implementation, and standardization 10 . Figure 2.…”

Section: Used Technologiesmentioning

confidence: 99%

RDF graph validation using rule-based reasoning

Meester

Heyvaert

Arndt

et al. 2020

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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.

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