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Project Histories: Managing Data Provenance Across Collection-Oriented Scientific Workflow Runs

  • Shawn Bowers
  • Timothy McPhillips
  • Martin Wu
  • Bertram Ludäscher
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4544)

Abstract

While a number of scientific workflow systems support data provenance, they primarily focus on collecting and querying provenance for single workflow runs. Scientific research projects, however, typically involve (1) many interrelated workflows (where data from one or more workflow runs are selected and used as input to subsequent runs) and (2) tasks between workflow runs that cannot be fully automated. This paper addresses the need for recording data dependencies across multiple workflow runs and accommodating data management activities performed between runs. We define a new conceptual model for representing project-level provenance based on the notion of project histories and folders, and describe mechanisms to support this model in the collection-oriented modeling and design framework of Kepler. Our approach allows users to conveniently organize their projects and data using the familiar folder-hierarchy metaphor, while at the same time integrating this information with detailed provenance of data products generated via automated scientific workflows.

Keywords

Hide Markov Model Dependency Graph Project History Read Scope Data Provenance 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Shawn Bowers
    • 1
  • Timothy McPhillips
    • 1
  • Martin Wu
    • 1
  • Bertram Ludäscher
    • 1
    • 2
  1. 1.UC Davis Genome Center, University of California, Davis 
  2. 2.Department of Computer Science, University of California, Davis 

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