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, hampering their comparison and an understanding of their benefits and limitations. In this paper, we strive for a better understanding of the key challenges that these systems must face and define a generic methodology to evaluate their performance. Specifically, we identify three Key Performance Indicators and seven commandments that specify how to design the stress tests for system evaluation. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Scharrenbach, T., Urbani, J., Margara, A., Della Valle, E., & Bernstein, A. (2013). Seven commandments for benchmarking semantic flow processing systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7882 LNCS, pp. 305–319). Springer Verlag. https://doi.org/10.1007/978-3-642-38288-8_21
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