ABSTRACT

In traditional Semantic Web reasoning data are usually static or quasistatic1, so the whole computation of the ontological entailment can be executed every time the data change. When we consider RDF streams the static hypothesis is not valid anymore: RDF stream engines work with highly dynamic data and they need to process them faster than new data arrives to avoid congestion states. In this scenario, traditional materialization techniques could fail; a possible solution is the incremental maintenance of the materialized entailment using adaptations of the classical DRed algorithm [128, 506]: when new triples are added, the deducible data is added to the materialization; similarly, when triples are deleted the triples that cannot be deducted anymore are removed from the entailment. The idea of incremental maintenance was previously delivered in the context of deductive databases, where logic programming was used for the incremental maintenance of such entailments. The idea of incrementally maintaining an ontological entailment was proposed

first by [553]: in this work the authors propose a version of DRed based on s logic program that computes the changes in the ontological entailment, and consequently computes the new materialization adding and removing the two delta sets.