Distributed Resolution for Description Logic Ontologies

knowledge representation on the Web has created new challenges with
respect to reasoning in these logics. In order to support the vision of a
semantic web of interrelated ontologies, reasoning procedures have to
be highly scalable and able to deal with physically distributed knowledge
models. A natural way of addressing these problems is to rely on distributed
inference procedures that can distribute the load between different solvers,
thus reducing potential bottlenecks both in terms of memory and computation
time. We propose a distributed resolution approach based on local resolution
and propagation of derived axioms between different reasoners.