An Evaluation of VIG with the BSBM Benchmark

We present an experimental evaluation of VIG, a data scaler for OBDA benchmarks. Data scaling is a relatively recent approach, proposed in the database community, that allows for scaling an input data instance to s times its size, while preserving certain application-specific characteristics. A data scaler is a “general” generator, in the sense that it can be re-used on different database schemas, and that users are not required to manually input the data characteristics. VIG lifts the scaling approach from the database level to the OBDA level, where the domain information of ontologies and mappings has to be taken into account as well. To evaluate VIG, in this paper we use it to generate data for the Berlin SPARQL Benchmark (BSBM), and compare it with the official BSBM data generator.