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Scaling SPADE to "Big Provenance"
Ashish Gehani, Hasanat Kazmi, and Hassaan Irshad, SRI International
Provenance middleware (such as SPADE) lets individuals and applications use a common framework for reporting, storing, and querying records that characterize the history of computational processes and resulting data artifacts. Previous efforts have addressed a range of issues, from instrumentation techniques to applications in the domains of scientific reproducibility and data security. Here we report on our experience adapting SPADE to handle large provenance data sets. In particular, we describe two motivating case studies, several challenges that arose from managing provenance at scale, and our approach to address each concern.
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title = {Scaling {SPADE} to "Big Provenance"},
booktitle = {8th USENIX Workshop on the Theory and Practice of Provenance (TaPP 16)},
year = {2016},
address = {Washington, D.C.},
url = {https://www.usenix.org/conference/tapp16/workshop-program/presentation/gehani},
publisher = {USENIX Association},
month = jun
}
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