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Yin & Yang: Demonstrating Complementary Provenance from noWorkflow & YesWorkflow

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9672)

Abstract

The noWorkflow and YesWorkflow toolkits both enable researchers to capture, store, query, and visualize the provenance of results produced by scripts that process scientific data. noWorkflow captures prospective provenance representing the program structure of Python scripts, and retrospective provenance representing key events observed during script execution. YesWorkflow captures prospective provenance declared through annotations in the comments of scripts, and supports key retrospective provenance queries by observing what files were used or produced by the script. We demonstrate how combining complementary information gathered by noWorkflow and YesWorkflow enables provenance queries and data lineage visualizations neither tool can provide on its own.

Keywords

Prospective Provenance Retrospective Provenance Provenance Queries Script Python Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Universidade Federal FluminenseNiteróiBrazil
  2. 2.University of California, DavisDavisUSA
  3. 3.University of Illinois, Urbana-ChampaignChampaignUSA
  4. 4.Université Paris-DauphineParisFrance
  5. 5.University of MassachusettsDartmouthUSA

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