Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Proceedings of the 17th international conference on World Wide Web
SPARQL basic graph pattern optimization using selectivity estimation
Proceedings of the 17th international conference on World Wide Web
RDF-3X: a RISC-style engine for RDF
Proceedings of the VLDB Endowment
Querying distributed RDF data sources with SPARQL
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
An evaluation of approaches to federated query processing over linked data
Proceedings of the 6th International Conference on Semantic Systems
FedX: optimization techniques for federated query processing on linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Improving the recall of live linked data querying through reasoning
RR'12 Proceedings of the 6th international conference on Web Reasoning and Rule Systems
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
SPARQL Endpoint Metrics for Quality-Aware Linked Data Consumption
Proceedings of International Conference on Information Integration and Web-based Applications & Services
Semantic-based QoS management in cloud systems: Current status and future challenges
Future Generation Computer Systems
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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 evaluation 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, techniques 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 efficient 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.