RWTH Aachen University
Automated generation of axioms from streaming data, such as traffic and text, can result in very large ontologies that single machine reasons cannot handle. Reasoning with large ontologies requires distributed solutions. Scalable reasoning techniques for RDFS, OWL horst and OWL 2 RL now exist. For OWL 2 EL, several distributed reasoning approaches have been tried, but are all perceived to be inefficient. The authors analyze this perception. They analyze completion rule based distributed approaches, using different characteristics, such as dependency among the rules, implementation optimizations, how axioms and rules are distributed.