Abstract
Over the last few years, the processing of dynamic data has gained increasing attention in the Semantic Web community. This led to the development of several stream reasoning systems that enable on-the-fly processing of semantically annotated data that changes over time. Due to their streaming nature, analyzing such systems is extremely difficult. Currently, their evaluation is conducted under heterogeneous scenarios, which makes it hard to clearly compare them, understanding the benefits and limitations of each of them. In this paper, we strive for a better understanding the key challenges that these systems must face and define a generic methodology to evaluate their performance. Specifically, we identify three Key Performance Indicators (KPIs) and seven commandments that specify how to design the stress tests for system evaluation.