Large-Scale Reasoning on Expressive Horn Ontologies

Carlo Allocca, Francesco Calimeri, Cristina Civili, Roberta Costabile, Bernardo Cuteri, Alessio Fiorentino, Davide Fuscà, Stefano Germano, Giovanni Laboccetta, Marco Manna, Simona Perri, Kristian Reale (+3 others)
2019 Datalog  
Efficient large-scale reasoning is a fundamental prerequisite for the development of the Semantic Web. In this scenario, it is convenient to reduce standard reasoning tasks to query evaluation over (deductive) databases. From a theoretical viewpoint much has been done. Conversely, from a practical point of view, only a few reasoning services have been developed, which however typically can only deal with lightweight ontologies. To fill the gap, the paper presents owl2dlv, a novel and modern
more » ... log system for evaluating SPARQL queries over very large OWL 2 knowledge bases. owl2dlv builds on the well-known ASP system dlv by incorporating novel optimizations sensibly reducing memory consumption and a server-like behavior to support multiplequery scenarios. The high potential of owl2dlv for large-scale reasoning is outlined by the results of an experiment on data-intensive benchmarks, and confirmed by the direct interest of a major international industrial player, which has stimulated and partially supported this work.
dblp:conf/datalog/AlloccaCCCCFFGL19 fatcat:4kvt6iqpozdnpptucfcpld536i