UP & DOWN: Improving Provenance Precision by Combining Workflow- and Trace-Level Information

Authors: 

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

Abstract: 

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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