Project histories: Managing data provenance across collection-oriented scientific workflow runs
- Shawn Bowers(corresponding author),
- Timothy McPhillips,
- Martin Wu,
- Bertram Ludäscher
- University of California, Davis,
- University of California
Open access
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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.
Bibliographic Information
Output type
Original language
EnglishPages from-to (Number of pages)
Pages 122-138 (17 pages)Publication milestones
- Published - 2007
Publication status
Publisher
Springer VerlagPublication series
- Publication series name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print): 0302-9743
ISSN (Electronic): 1611-3349
Volume: 4544 LNBI
ISBN (Print)
3540732543, 9783540732549Publication IDs
- Scopus: 34547452653
