Evaluating Datalog Tools for Meta-reasoning over OWL 2 QL

There has been increasing interest in enriching ontologies with meta-modeling and meta-querying for the past few years. Unfortunately, the Direct Semantics for OWL2 and SPARQL does not support meta-constructs in a satisfactory way: While meta-axioms (involving identifiers used both as a class and an individual) can be syntactically expressed using punning, different occurrences of the same identifier will be treated as different entities. For example, GoldenEagle used as an instance of EndangeredSpecies and also as a class containing individuals, will be treated as two separate, unrelated entities. Meta-queries (for example, asking for classes that also occur as individuals) are not allowed at all in SPARQL under the Direct Semantics Entailment Regime. To overcome this, a new semantic flavour for SPARQL, called Meta-modeling Semantics Entailment Regime (MSER), has been introduced. In previous work, Cima et al. have proposed a reduction from OWL 2 QL (a light-weight profile of OWL 2) and associated meta-queries in SPARQL to query answering over Datalog rules. In this paper, we experiment with various logic programming tools that support Datalog querying to determine their suitability as back-ends to MSER query answering. These tools stem from different logic programming paradigms (Prolog, pure Datalog, Answer Set Programming). Our work shows that the Datalog approach to MSER querying is practical also for sizeable ontologies.