@conference {156,
	title = {Distributed and Scalable OWL EL Reasoning},
	booktitle = {Proceedings of the 12th Extended Semantic Web Conference (ESWC 2015) },
	year = {2015},
	publisher = {Springer},
	organization = {Springer},
	address = {Portoroz, Slovenia},
	abstract = {<p class="rtejustify">OWL 2 EL is one of the tractable proles of the Web Ontology\&nbsp;Language (OWL) which is a W3C-recommended standard. OWL 2\&nbsp;EL provides sucient expressivity to model large biomedical ontologies\&nbsp;as well as streaming data such as trac, while at the same time allows\&nbsp;for ecient reasoning services. Existing reasoners for OWL 2 EL, however,\&nbsp;use only a single machine and are thus constrained by memory and\&nbsp;computational power. At the same time, the automated generation of\&nbsp;ontological information from streaming data and text can lead to very\&nbsp;large ontologies which can exceed the capacities of these reasoners. We\&nbsp;thus describe a distributed reasoning system that scales well using a cluster\&nbsp;of commodity machines. We also apply our system to a use case on\&nbsp;city trac data and show that it can handle volumes which cannot be\&nbsp;handled by current single machine reasoners.</p>
},
	keywords = {DistEL, Distributed Reasoning, Ontology Classification, OWL EL},
	author = {Raghava Mutharaju and Pascal Hitzler and Prabhaker Mateti and Freddy L{\'e}cu{\'e}}
}
@conference {10,
	title = {DistEL: A Distributed EL+ Ontology Classifier},
	booktitle = {Proceedings of the 9th International Workshop on Scalable Semantic Web Knowledge Base Systems, co-located with the International Semantic Web Conference (ISWC 2013)},
	volume = {1046},
	year = {2013},
	month = {10/2013},
	pages = {17-32},
	publisher = {CEUR-WS.org},
	organization = {CEUR-WS.org},
	address = {Sydney, Australia},
	abstract = {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.},
	keywords = {Classification, DistEL, Distributed Reasoning, EL+, OWL, Scalability},
	author = {Raghava Mutharaju and Pascal Hitzler and Prabhaker Mateti},
	editor = {Thorsten Liebig and Achille Fokoue}
}
