  Several centralised RDF systems support datalog reasoning by precomputing and
storing all logically implied triples using the wellknown seminaive algorithm.
Large RDF datasets often exceed the capacity of centralised RDF systems, and a
common solution is to distribute the datasets in a cluster of shared-nothing
servers. While numerous distributed query answering techniques are known,
distributed seminaive evaluation of arbitrary datalog rules is less understood.
In fact, most distributed RDF stores either support no reasoning or can handle
only limited datalog fragments. In this paper we extend the dynamic data
exchange approach for distributed query answering by Potter et al. [12] to a
reasoning algorithm that can handle arbitrary rules while preserving important
properties such as nonrepetition of inferences. We also show empirically that
our algorithm scales well to very large RDF datasets
