From computation models to models of provenance: The RWS approach

Bertram Ludäscher, Norbert Podhorszki, Ilkay Altintas, Shawn Bowers, Timothy McPhillips

Research output: Contribution to journalArticlepeer-review

Abstract

Scientific workflows often benefit from or even require advanced modeling constructs, e.g. nesting of subworkflows, cycles for executing loops, data-dependent routing, and pipelined execution. In such settings, an often overlooked aspect of provenance takes center stage: a suitable model of provenance (MoP) for scientific workflows should be based upon the underlying model of computation (MoC) used for executing the workflows. We can derive an adequate MoP from a MoC (such as Kahn's process networks) by taking into account the assumptions that a MoC entails, and by recording the observables which it affords. In this way, a MoP captures or at least better approximates 'real' data dependencies for workflows with advanced modeling constructs. As a specific instance, we elaborate on the Read-Write-ReSet model, a simple and flexible MoP suitable for a number of different MoCs.

Original languageEnglish (US)
Pages (from-to)507-518
Number of pages12
JournalConcurrency Computation Practice and Experience
Volume20
Issue number5
DOIs
StatePublished - Apr 10 2008
Externally publishedYes

Keywords

  • Computation model
  • Provenance
  • Scientific workflow

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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