SUMA: A Partial Materialization-Based Scalable Query Answering in OWL 2 DL

Abstract Ontology-mediated querying (OMQ) provides a paradigm for query answering according to which users not only records at the database but also implicit information inferred from ontology. A key challenge in OMQ is that may be infinite, cannot stored and queried by off -the -shelf engine. The commonly adopted technique deal with infinite entailments rewriting, which, however, comes cost of rewriting runtime. In this work, partial materialization method proposed ensure extension always finite. technology does rewrite instead computes consequences entailed ontology before online query. Besides, analysis algorithm designed completeness rooted Boolean conjunctive queries over materialization. We soundly incompletely expand our support highly expressive language, OWL 2 DL. Finally, we further optimize efficiency role implement approach as prototype system SUMA integrating off-the-shelf efficient SPARQL experiments show complete on each test query, same Pellet outperforms PAGOdA. scalable large datasets.