Title
Karma2: Provenance Management For Data-Driven Workflows
Abstract
The increasing ability for the sciences to sense the world around its is resulting it? a growing need for data-driven e-Science applications that are under the control of workflows composed of services on the Grid. The focus of our work is on provenance collection for these workflows that are necessary to validate the workflow and to determine quality of generated data products. The challenge we address is to record uniform and usable provenance metadata that meets the domain needs while minimizing the modification burden on the set-vice authors and the performance overhead on the workflow engine and the services. The framework is based on generating discrete provenance activities during the lifecycle of a workflow execution that can be aggregated to form complex data and process provenance graphs that can span across workflows. The implementation uses a loosely coupled publish-subscribe architecture for propagating these activities, and the capabilities of the system satisfy the needs of detailed provenance collection. A performance evaluation of a prototype finds a minimal performance overhead (in the range of 1% or an eight-service workflow using 2 71 data products).
Year
DOI
Venue
2008
10.4018/jwsr.2008040101
INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH
Keywords
Field
DocType
data management, metadata, process mining, provenance, work-flows
USable,Data mining,Metadata,Computer science,e-Science,Workflow engine,Workflow,Data management,Grid,Database,Process mining
Journal
Volume
Issue
ISSN
5
2
1545-7362
Citations 
PageRank 
References 
87
3.24
6
Authors
3
Name
Order
Citations
PageRank
Yogesh Simmhan11904134.15
Beth Plale21837142.80
Dennis Gannon32514330.26