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arXiv:1911.00598cs.AI

SHACL Constraints with Inference Rules

Paolo Pareti, George Konstantinidis, Timothy J. Norman, Murat Şensoy

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Abstract

The Shapes Constraint Language (SHACL) has been recently introduced as a W3C recommendation to define constraints that can be validated against RDF graphs. Interactions of SHACL with other Semantic Web technologies, such as ontologies or reasoners, is a matter of ongoing research. In this paper we study the interaction of a subset of SHACL with inference rules expressed in datalog. On the one hand, SHACL constraints can be used to define a "schema" for graph datasets. On the other hand, inference rules can lead to the discovery of new facts that do not match the original schema. Given a set of SHACL constraints and a set of datalog rules, we present a method to detect which constraints could be violated by the application of the inference rules on some graph instance of the schema, and update the original schema, i.e, the set of SHACL constraints, in order to capture the new facts that can be inferred. We provide theoretical and experimental results of the various components of our approach.

arXiv comments
Journal reference
In International Semantic Web Conference, pp. 539-557. Springer, Cham, 2019
DOI
doi:10.1007/978-3-030-30793-6_31
Subjects
cs.AIArtificial Intelligence cs.DBDatabases

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