M. Tamer Özsu

University of Waterloo

"RDF Data Management Using Graph Algorithms"

 

Abstract:

Resource Description Framework (RDF) has been proposed for modeling Web objects as part of developing the"semantic web". It has also gained attention as a way to accomplish web data integration. As the volume of RDF data has increased, interesting data management issues have arisen. In this talk I will discuss some of our recent work in this area, focusing on two results: answering SPARQL queries over RDF graphs, and processing aggregate SPARQL queries. The first problem focuses on evaluating SPARQL queries with wildcards over an RDF graph that sees frequent updates. We propose an approach that maps both the RDF data and the SPARQL query into graphs and converts the query evaluation problem to one of subgraph matching. In order to speed up query processing, we propose an indexing mechanism and pruning rules to reduce the search space. The second problem addresses the processing of aggregation queries over large RDF data sets. We propose a processing approach that partitions aggregate queries into smaller parts (called star queries), processes these efficiently, and joins the results of star queries to obtain more general results. We develop indexes to assist in executing star queries and to facilitate joining their results.

Bio:

M. Tamer Özsu is Professor of Computer Science at the David R. Cheriton School of Computer Science of the University of Waterloo. His research is in data management focusing on large-scale data distribution and management of non-traditional data. He is a Fellow of the Association for Computing Machinery (ACM), and of the Institute of Electrical and Electronics Engineers (IEEE), and a member of Sigma Xi.

___________________________________________________________________________