A Rule System for Querying Persistent RDFS Data

Abstract

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.