Purely Synthetic and Domain Independent Consistency-Guaranteed Populations in $\mathcal {SHIQ}^{(\mathcal {D})}$

Abstract

The elaborations of artificial knowledge bases can represent a clever solution to test new semantics-based infrastructures before deploying them and a precious support to the design of some prototypes. One major challenge of such synthetic data generations is to guarantee the acquisition of sound knowledge bases able to pass the equivalent of a Turing test. That’s why populations have to be restricted to guarantee the consistency until a certain fragment of expressivity. In a past work, we released a first version of a populator guaranteeing the consistency and populating knowledge bases founded on $\textsc {TBox}$es expressed in $\mathcal {ALCQ}^{(\mathcal {D})}$. This purely syntactic and domain independent populator is based on a random process of concept, role and limited data instantiations. In this paper, we propose to extend the expressivity covering by the populator until the fragment $\mathcal {SHIQ}^{(\mathcal {D})}$. This extension deals with $\textsc {Rbox}$es conforming the consistency of the role assertions with respect to the domains/ranges, the universal quantifications and the maximal cardinalities of all the super and inverse roles. Finally, an evaluation of some performances of the populator has been performed.