TY - CONF T1 - Distributed and Scalable OWL EL Reasoning T2 - Proceedings of the 12th Extended Semantic Web Conference (ESWC 2015) Y1 - 2015 A1 - Raghava Mutharaju A1 - Pascal Hitzler A1 - Prabhaker Mateti A1 - Freddy Lécué KW - DistEL KW - Distributed Reasoning KW - Ontology Classification KW - OWL EL AB -

OWL 2 EL is one of the tractable proles of the Web Ontology Language (OWL) which is a W3C-recommended standard. OWL 2 EL provides sucient expressivity to model large biomedical ontologies as well as streaming data such as trac, while at the same time allows for ecient reasoning services. Existing reasoners for OWL 2 EL, however, use only a single machine and are thus constrained by memory and computational power. At the same time, the automated generation of ontological information from streaming data and text can lead to very large ontologies which can exceed the capacities of these reasoners. We thus describe a distributed reasoning system that scales well using a cluster of commodity machines. We also apply our system to a use case on city trac data and show that it can handle volumes which cannot be handled by current single machine reasoners.

JF - Proceedings of the 12th Extended Semantic Web Conference (ESWC 2015) PB - Springer CY - Portoroz, Slovenia ER - 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 - Very Large Scale OWL Reasoning through Distributed Computation T2 - 11th International Semantic Web Conference (ISWC 2012), Proceedings, Part II Y1 - 2012 A1 - Raghava Mutharaju ED - Philippe Cudré-Mauroux ED - Jeff Heflin ED - Evren Sirin ED - Tania Tudorache ED - Jérôme Euzenat ED - Manfred Hauswirth ED - Josiane Xavier Parreira ED - James A. Hendler ED - Guus Schreiber ED - Abraham Bernstein ED - Eva Blomqvist KW - Distributed Reasoning KW - Ontology Classification KW - OWL EL AB -

Due to recent developments in reasoning algorithms of the various OWL profiles, the classification time for an ontology has come down drastically. For all of the popular reasoners, in order to process an ontology, an implicit assumption is that the ontology should fit in primary memory. The memory requirements for a reasoner are already quite high, and considering the ever increasing size of the data to be processed and the goal of making reasoning Web scale, this assumption becomes overly restrictive. In our work, we study several distributed classification approaches for the description logic EL+ (a fragment of OWL 2 EL profile). We present the lessons learned from each approach, our current results, and plans for future work.

JF - 11th International Semantic Web Conference (ISWC 2012), Proceedings, Part II PB - Springer CY - Boston, MA, USA VL - 7650 UR - http://dx.doi.org/10.1007/978-3-642-35173-0_30 ER -