The Berlin SPARQL Benchmark (BSBM) is a suite of benchmarks built around an e-commerce use case [1]. We generated 21 versions of the dataset with different scale factors. The first dataset, with a scale factor of 100, contains about 7,000 vertices and 75,000 edges. We generated versions with scale factors between 2,000 and 40,000 in steps of 2,000. The largest dataset contains about 1.3 M vertices and 13 M edges. For our experiments in [2], we first use the different versions ordered from smallest to largest (version 0 to 20) to simulate a growing graph database. Subsequently, we reverse the order to emulate a shrinking graph database. Over all versions, the mean degree is 8.1 (+- 0.5), the mean in-degree is 4.6 (+- 0.3), and the mean out-degree is 9.8 (+- 0.2). 1. Christian Bizer, Andreas Schultz: The Berlin SPARQL Benchmark. Int. J. Semantic Web Inf. Syst. 5(2): 1-24 (2009) 2. Till Blume, David Richerby, Ansgar Scherp: Incremental and Parallel Computation of Structural Graph Summaries for Evolving Graphs. CIKM 2020: 75-84

{"references": ["Christian Bizer, Andreas Schultz: The Berlin SPARQL Benchmark. Int. J. Semantic Web Inf. Syst. 5(2): 1-24 (2009)", "Till Blume, David Richerby, Ansgar Scherp: Incremental and Parallel Computation of Structural Graph Summaries for Evolving Graphs. CIKM 2020: 75-84"]}