A Rule-Based Object-Oriented OWL Reasoner
IEEE Transactions on Knowledge and Data Engineering
μOR --- A Micro OWL DL Reasoner for Ambient Intelligent Devices
GPC '09 Proceedings of the 4th International Conference on Advances in Grid and Pervasive Computing
DLEJena: A practical forward-chaining OWL 2 RL reasoner combining Jena and Pellet
Web Semantics: Science, Services and Agents on the World Wide Web
Efficient inferencing for OWL EL
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
CEL: a polynomial-time reasoner for life science ontologies
IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning
FaCT++ description logic reasoner: system description
IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning
CADE' 20 Proceedings of the 20th international conference on Automated Deduction
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Embedded EL + reasoning on programmable logic controllers
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part II
Hi-index | 0.00 |
Ontologies have been used for formal representation of knowledge for many years now. One possible knowledge representation language for ontologies is the OWL 2 Web Ontology Language, informally OWL 2. The OWL specification includes the definition of variants of OWL, with different levels of expressiveness. OWL DL and OWL Lite are based on Description Logics, for which sound and complete reasoners exits. Unfortunately, all these reasoners are too complex for embedded systems. But since evaluation of ontologies on these resource constrained devices becomes more and more necessary (e.g. for diagnostics) we developed an OWL reasoner for embedded devices. We use the OWL 2 sub language OWL 2 RL, which can be implemented using rule-based reasoning engines. In this paper we present our used embedded hardware, the implemented reasoning component, and results regarding performance and memory consumption.