Yin & Yang: Demonstrating complementary provenance from noWorkflow & yesWorkflow

João Felipe Pimentel, Saumen Dey, Timothy McPhillips, Khalid Belhajjame, David Koop, Leonardo Murta, Vanessa Braganholo, Bertram Ludäscher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProvenance and Annotation of Data and Processes - 6th International Provenance and Annotation Workshop, IPAW 2016, Proceedings
EditorsBoris Glavic, Marta Mattoso
PublisherSpringer-Verlag Berlin Heidelberg
Pages161-165
Number of pages5
ISBN (Print)9783319405926
DOIs
StatePublished - 2016
Event6th International Provenance and Annotation Workshop, IPAW 2016 - McLean, United States
Duration: Jun 7 2016Jun 8 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9672
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Provenance and Annotation Workshop, IPAW 2016
CountryUnited States
CityMcLean
Period6/7/166/8/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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