Distributed RDFS knowledge-based system update in case of deletions

This article presents a method for maintaining the materialization of a RDFS Knowledge-Base in case of fact deletions in a distributed way. MapReduce framework is used to implement and test the method. Current MapReduce framework-based distributed reasoning is used for static RDFS knowledge bases. However, any changes in KB have been followed by rebuilding the closure which is very time consuming. The alternative is to update it. The method preserves soundness and completeness which are necessary conditions to any materialization process. The steps involved in fact deletion is recognized and a set of RDFS rules is devised accordingly to preserve correctness properties. Finally, we analyze the time and space consumed by the presented method.