@inproceedings{iann-etal-2009-GiaBATA,
	Abstract = {In this demo we present GiaBATA, a system for storing, aggregating, and querying Semantic Web data, based on declarative logic programming technology, namely on the dlvhex system, which allows us to implement a fully SPARQL compliant semantics, and on DLVDB , which extends the DLV system with persistent storage capabilities. Compared with off-the-shelf RDF stores and SPARQL engines, we offer more flexible support for rule-based RDFS and other higher entailment 
regimes by enabling custom reasoning via rules, and the possibility to choose the reference ontology on a per query basis. Due to the declarative approach, GiaBATA gains the possibility to apply well-known logic-level optimization features of logic programming (LP) and deductive database systems. Moreover, our architecture allows for extensions of SPARQL by non-standard features such as aggregates, custom built-ins, or arbitrary rulesets. With the resulting system we provide 
a flexible toolbox that embeds Semantic Web data and ontologies in a fully declarative LP environment.},
	Address = {Heraklion, Greece},
	Author = {Giovambattista Ianni and Thomas Krennwallner and Alessandra Martello and Axel Polleres},
	Booktitle = {Proceedings of the 6th European Semantic Web Conference (ESWC2009)},
	Day = {31--4},
	Month = MAY,
	Note = {Demo Paper},
	Projects = {incontext,lion2},
	Publisher = {Springer},
	Title = {A Rule System for Querying Persistent RDFS Data},
	Type = OTHER,
	Url = {http://www.polleres.net/publications/iann-etal-2009-GiaBATA.pdf},
	Year = 2009,
	Bdsk-Url-1 = {http://www.polleres.net/publications/iann-etal-2009-GiaBATA.pdf}}

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Compared with off-the-shelf RDF stores and SPARQL engines, we offer more flexible support for rule-based RDFS and other higher entailment regimes by enabling custom reasoning via rules, and the possibility to choose the reference ontology on a per query basis. Due to the declarative approach, GiaBATA gains the possibility to apply well-known logic-level optimization features of logic programming (LP) and deductive database systems. Moreover, our architecture allows for extensions of SPARQL by non-standard features such as aggregates, custom built-ins, or arbitrary rulesets. 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