Transitivity Reasoning for RDF Ontology with Iterative MapReduce

As growing of the Web, there are many efforts to use knowledge in formal language. The most popular work of the formal language is "LOD(linked open data)" initiative based on RDF(s). Most previous work for RDFs Reasoning is based on single reasoning machine. However, reasoning for large volume of RDFs is became a challenging issue as increasing of RDFs dataset such as LOD because previous work such as Jena can\´t handle the large scale of RDF dataset in the Internet. Transitivity reasoning which is most complicated one of RDFs reasoning rules generates monotone increasing dataset (transitive closure) continuously. This work proposes distributed reasoning method for large scale of RDFs dataset based on MapReduce algorithm. We analysis distributed RDFs reasoning and propose a distributed reasoning method. We implement the proposed method and reveals experimental results to show performance of our method.