UP & DOWN: Improving Provenance Precision by Combining Workflow- and Trace-Level Information
Saumen Dey, University of California, Davis; Khalid Belhajjame, Université Paris-Dauphine; David Koop, New York University; Tianhong Song, University of California, Davis; Paolo Missier, Newcastle University; Bertram Ludäscher, University of California, Davis
Workflow-level provenance declarations can improve the precision of coarse provenance traces by reducing the number of “false” dependencies (not every output of a step depends on every input). Conversely, fine-grained execution provenance can be used to improve the precision of input-output dependencies of workflow actors. We present a new logic-based approach for improving provenance precision by combining downward and upward inference, i.e., from workflows to traces and vice versa.
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author = {Saumen Dey and Khalid Belhajjame and David Koop and Tianhong Song and Paolo Missier and Bertram Lud{\"a}scher},
title = {{UP} \& {DOWN}: Improving Provenance Precision by Combining Workflow- and {Trace-Level} Information},
booktitle = {6th USENIX Workshop on the Theory and Practice of Provenance (TaPP 2014)},
year = {2014},
address = {Cologne},
url = {https://www.usenix.org/conference/tapp2014/agenda/presentation/dey},
publisher = {USENIX Association},
month = jun
}