A crucial challenge for scientific workflow management systems is to support the efficient and scalable storage and querying of large provenance datasets that record the history of in silico experiments. As new provenance management systems are being developed, it is important to have benchmarks that can evaluate these systems and provide an unbiased comparison. In this paper, based on the requirements for scientific workflow provenance systems, we design an extensible benchmark that features a collection of techniques and tools for workload generation, query selection, performance measurement, and experimental result interpretation.
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