RDF graphs are commonly derived from (semi-)structured data by applying a set of mappings. RDF graph construction is performed by either materialising or virtualising an RDF graph and several benchmarks were purposed to measure their performance. However, even though significantly more materialisation systems exist, most benchmarks focus on virtualisation systems. Materialisation benchmarks are currently derived from virtualisation benchmarks, overlooking parameters that affect materialisation systems. In this paper, we introduce KROWN, a new benchmark to investigate the impact of datasets and mappings on RDF materialisation. We establish several benchmark scenarios with various scaling parameters to measure the execution time and computing resources, e.g., CPU time, and memory consumption. Through this work, we have now a benchmark suitable for materialisation systems which allows to execute each system in a reproducible pipeline through our execution framework. Thanks to our benchmark, we identified parameters which heavily influence the execution of materialisation systems and no optimizations were explored for them so far. GitHub: https://github.com/kg-construct/KROWN Results: https://zenodo.org/doi/10.5281/zenodo.10973891