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.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {184663,
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
}
Download
Dey PDF