Towards Scalable and Complete Query Explanation with OWL 2 EL Ontologies

Zhe Wang, Mahsa Chitsaz, Kewen Wang, Jianfeng Du
2015 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management - CIKM '15  
Ontology-mediated data access and management systems are rapidly emerging. Besides standard query answering, there is also a need for such systems to be coupled with explanation facilities, in particular to explain missing query answers (i.e. desired answers of a query which are not derivable from the given ontology and data). This support is highly demanded for debugging and maintenance of big data, and both theoretical results and algorithms proposed. However, existing query explanation
more » ... thms either cannot scale over relative large data sets or are not guaranteed to compute all desired explanations. To the best of our knowledge, no existing algorithm can efficiently and completely explain conjunctive queries (CQs) w.r.t. ELH ⊥ ontologies. In this paper, we present a hybrid approach to achieve this. An implementation of the proposed query explanation algorithm has been developed using an off-the-shelf Prolog engine and a datalog engine. Finally, the system is evaluated over practical ontologies. Experimental results show that our system scales over large data sets.
doi:10.1145/2806416.2806547 dblp:conf/cikm/WangCWD15 fatcat:klcjrmqe5ndltgrdo32je7stea