FedX: A Federation Layer for Distributed Query Processing on Linked Open Data

Abstract. Driven by the success of the Linked Open Data initiative today’s Semantic Web is best characterized as a Web of interlinked datasets. Hand in hand with this structure new challenges to query processing are arising. Especially queries for which more than one data source can contribute results require advanced optimization and evalua-tion approaches, the major challenge lying in the nature of distribution: Heterogenous data sources have to be integrated into a federation to globally appear as a single repository. On the query level, though, tech-niques have to be developed to meet the requirements of efficient query computation in the distributed setting. We present FedX, a project which extends the Sesame Framework with a federation layer that enables ef-ficient query processing on distributed Linked Open Data sources. We discuss key insights to its architecture and summarize our optimization techniques for the federated setting. The practicability of our system will be demonstrated in various scenarios using the Information Workbench.