Extending largeRDFBench for multi-source data at scale for SPARQL endpoint federation

Querying the Web of Data is highly motivated by the use of federation approaches mainly SPARQL query federation when the data is available through endpoints. Different benchmarks have been proposed to exploit the full potential of SPARQL query federation approaches in real world scenarios with their limitations in size and complexity. Previously, we introduced LargeRDFBench – a billion-triple benchmark for SPARQL query federation. In this work, we pinpoint some of of the limitation of LargeRDFBench and propose an extension with 8 additional queries. Our evaluation results of the state-of-the-art federation engines revealed interesting insights, when tested on these additional queriesThis work was supported by the project HOBBIT, which has received funding from the European Union’s H2020 research and innovation action program (GA number 688227). Also, this publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289, co-funded by the European Regional Development Fund