On index merging for semantic web data

In this paper we explore the properties of description indices that store concept descriptions rather than plain data. Although these novel data structures are beneficial for efficiently answering semantic web queries, expressed in a language such as nRQL or SPARQL-DL, they take extra storage and their maintenance can become a performance bottleneck. In order to alleviate these shortcomings, we introduce a procedure for merging description indices. Experimental results over the LUBM benchmark show that this technique can result in economy of storage space, while the performance is slightly affected for a static workload and is improved for a dynamic workload.