Pay−as−you−go ontology query answering using a datalog reasoner
We describe a hybrid approach to conjunctive query answering over OWL 2 ontologies that combines a datalog reasoner with a fully-fledged OWL 2 reasoner in order to provide scalable “pay as you go” performance. Our approach delegates the bulk of the computation to the highly scalable datalog engine a...
| Main Authors: | , , , |
|---|---|
| Format: | Conference item |
| Language: | English |
| Published: |
CEUR-WS.org
2014
|
| Summary: | We describe a hybrid approach to conjunctive query answering over OWL 2 ontologies that combines a datalog reasoner with a
fully-fledged OWL 2 reasoner in order to provide scalable “pay as you
go” performance. Our approach delegates the bulk of the computation
to the highly scalable datalog engine and resorts to expensive OWL 2
reasoning only as necessary to fully answer the query. We have implemented a prototype system that uses RDFox as a datalog reasoner, and
HermiT as an OWL 2 reasoner. Our evaluation over both benchmark and
realistic ontologies and datasets suggests the feasibility of our approach. |
|---|