  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.

Artificial Intelligence;Databases