TY - CONF T1 - Distributed OWL EL Reasoning: The Story So Far T2 - Proceedings of the 10th International Workshop on Scalable Semantic Web Knowledge Base Systems, Riva Del Garda, Italy Y1 - 2014 A1 - Raghava Mutharaju A1 - Pascal Hitzler A1 - Prabhaker Mateti ED - Thorsten Liebig ED - Achille Fokoue KW - Distributed Reasoning KW - OWL EL KW - Scalability AB -

Automated generation of axioms from streaming data, such as traffic and text, can result in very large ontologies that single machine reasoners cannot handle. Reasoning with large ontologies requires distributed solutions. Scalable reasoning techniques for RDFS, OWL Horst and OWL 2 RL now exist. For OWL 2 EL, several distributed reasoning approaches have been tried, but are all perceived to be inefficient. We analyze this perception. We analyze completion rule based distributed approaches, using different characteristics, such as dependency among the rules, implementation optimizations, how axioms and rules are distributed. We also present a distributed queue approach for the classification of ontologies in description logic EL+ (fragment of OWL 2 EL).

JF - Proceedings of the 10th International Workshop on Scalable Semantic Web Knowledge Base Systems, Riva Del Garda, Italy PB - CEUR-WS.org CY - Riva del Garda, Italy VL - 1261 ER - TY - CONF T1 - DistEL: A Distributed EL+ Ontology Classifier T2 - Proceedings of the 9th International Workshop on Scalable Semantic Web Knowledge Base Systems, co-located with the International Semantic Web Conference (ISWC 2013) Y1 - 2013 A1 - Raghava Mutharaju A1 - Pascal Hitzler A1 - Prabhaker Mateti ED - Thorsten Liebig ED - Achille Fokoue KW - Classification KW - DistEL KW - Distributed Reasoning KW - EL+ KW - OWL KW - Scalability AB - OWL 2 EL ontologies are used to model and reason over data from diverse domains such as biomedicine, geography and road traffic. Data in these domains is increasing at a rate quicker than the increase in main memory and computation power of a single machine. Recent efforts in OWL reasoning algorithms lead to the decrease in classification time from several hours to a few seconds even for large ontologies like SNOMED CT. This is especially true for ontologies in the description logic EL+ (a fragment of the OWL 2 EL profile). Reasoners such as Pellet, Hermit, ELK etc. make an assumption that the ontology would fit in the main memory, which is unreasonable given projected increase in data volumes. Increase in the data volume also necessitates an increase in the computation power. This lead us to the use of a distributed system, so that memory and computation requirements can be spread across machines. We present a distributed system for the classification of EL+ ontologies along with some results on its scalability and performance. JF - Proceedings of the 9th International Workshop on Scalable Semantic Web Knowledge Base Systems, co-located with the International Semantic Web Conference (ISWC 2013) PB - CEUR-WS.org CY - Sydney, Australia VL - 1046 ER -