<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Prabhaker Mateti</style></author><author><style face="normal" font="default" size="100%">Freddy Lécué</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Distributed and Scalable OWL EL Reasoning</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 12th Extended Semantic Web Conference (ESWC 2015) </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DistEL</style></keyword><keyword><style  face="normal" font="default" size="100%">Distributed Reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL EL</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Portoroz, Slovenia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;OWL 2 EL is one of the tractable proles of the Web Ontology&amp;nbsp;Language (OWL) which is a W3C-recommended standard. OWL 2&amp;nbsp;EL provides sucient expressivity to model large biomedical ontologies&amp;nbsp;as well as streaming data such as trac, while at the same time allows&amp;nbsp;for ecient reasoning services. Existing reasoners for OWL 2 EL, however,&amp;nbsp;use only a single machine and are thus constrained by memory and&amp;nbsp;computational power. At the same time, the automated generation of&amp;nbsp;ontological information from streaming data and text can lead to very&amp;nbsp;large ontologies which can exceed the capacities of these reasoners. We&amp;nbsp;thus describe a distributed reasoning system that scales well using a cluster&amp;nbsp;of commodity machines. We also apply our system to a use case on&amp;nbsp;city trac data and show that it can handle volumes which cannot be&amp;nbsp;handled by current single machine reasoners.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Philippe Cudré-Mauroux</style></author><author><style face="normal" font="default" size="100%">Jeff Heflin</style></author><author><style face="normal" font="default" size="100%">Evren Sirin</style></author><author><style face="normal" font="default" size="100%">Tania Tudorache</style></author><author><style face="normal" font="default" size="100%">Jérôme Euzenat</style></author><author><style face="normal" font="default" size="100%">Manfred Hauswirth</style></author><author><style face="normal" font="default" size="100%">Josiane Xavier Parreira</style></author><author><style face="normal" font="default" size="100%">James A. Hendler</style></author><author><style face="normal" font="default" size="100%">Guus Schreiber</style></author><author><style face="normal" font="default" size="100%">Abraham Bernstein</style></author><author><style face="normal" font="default" size="100%">Eva Blomqvist</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Very Large Scale OWL Reasoning through Distributed Computation</style></title><secondary-title><style face="normal" font="default" size="100%">11th International Semantic Web Conference (ISWC 2012), Proceedings, Part II</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Distributed Reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL EL</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-35173-0_30</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston, MA, USA</style></pub-location><volume><style face="normal" font="default" size="100%">7650</style></volume><pages><style face="normal" font="default" size="100%">407–414</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;Due to recent developments in reasoning algorithms of the&amp;nbsp;various OWL profiles, the classification time for an ontology has come&amp;nbsp;down drastically. For all of the popular reasoners, in order to process&amp;nbsp;an ontology, an implicit assumption is that the ontology should fit in&amp;nbsp;primary memory. The memory requirements for a reasoner are already&amp;nbsp;quite high, and considering the ever increasing size of the data to be&amp;nbsp;processed and the goal of making reasoning Web scale, this assumption&amp;nbsp;becomes overly restrictive. In our work, we study several distributed&amp;nbsp;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.&lt;/p&gt;
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