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Federation of semantic data on SPARQL endpoints will allow data to remain distributed so that it can be controlled by local curators and swiftly updated. There are considerable performance problems, which the present work proposes to address, mainly by computation and exposure of statistical digests to assist selectivity estimation. For an objective evaluation as well as comparison of engines, benchmarks that exhaustively covers the parameter space is required. We propose an investigation into this problem using statistical experimental planning.The Semantic Web: Research and Applications. Lecture Notes in Computer Science Volume 7295, 2012, pp 828-832. The final publication is available at Springe

Sharing Statistics for SPARQL Federation Optimization, with Emphasis on Benchmark Quality