Ontology−based Query Answering with PAGOdA
Yujiao Zhou, Yavor Nenov, Bernardo Cuenca Grau, Ian Horrocks · 2015
We describe PAGOdA: a highly optimised ‘pay-as-you-go’ reasoning system that supports conjunctive query (CQ) answering with respect to an arbitrary OWL 2 ontology and an RDF dataset. PAGOdA uses a novel hybrid approach to query answering that combines a datalog reasoner (currently RDFox [10]) with a fullyfledged OWL 2 reasoner (currently HermiT [5]) to provide scalable performance while still guaranteeing sound and complete answers. PAGOdA delegates the bulk of the computational workload to the datalog reasoner, with the extent to which the fully-fledged reasoner is needed depending on interactions between the ontology, the dataset and the query. Thus, even when using a very expressive ontology, queries can often be fully answered using only the datalog reasoner; and even when the fully-fledged reasoner is required, PAGOdA employs a range of optimisations to reduce the number and size of the relevant reasoning problems.