Large-Scale Reasoning with OWL [article]

Michael Ruster
2016 arXiv   pre-print
With the growth of the Semantic Web in size and importance, more and more knowledge is stored in machine-readable formats such as the Web Ontology Language OWL. This paper outlines common approaches for efficient reasoning on large-scale data consisting of billions (10^9) of triples. Therefore, OWL and its sublanguages, as well as forward and backward chaining techniques are presented. The WebPIE reasoner is discussed in detail as an example for forward chaining using MapReduce for
more » ... on. Moreover, the QueryPIE reasoner is presented as a backward chaining/hybrid approach which uses query rewriting. Furthermore, an overview on other reasoners is given such as OWLIM and TrOWL.
arXiv:1602.04473v1 fatcat:4b3gdsoct5ge3a5txqw2ah23cu