The increasing ability for the sciences to sense the world around
us is resulting in a growing need for datadriven 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 work-flow 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 service 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% for an eight-service workflow using
271 data products).
%0 Journal Article
%1 Simmhan:ijwsr:2008
%A Simmhan, Yogesh L.
%A Plale, Beth
%A Gannon, Dennis
%D 2008
%I IGI Publishing
%J International Journal of Web Services Research (IJWSR)
%K escience, karma, msr, peer provenance, reviewed workflow,
%N 2
%P 1--22
%R 10.4018/jwsr.2008040101
%T Karma2: Provenance Management for Data-Driven Workflows
%V 5
%X The increasing ability for the sciences to sense the world around
us is resulting in a growing need for datadriven 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 work-flow 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 service 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% for an eight-service workflow using
271 data products).
@article{Simmhan:ijwsr:2008,
abstract = {The increasing ability for the sciences to sense the world around
us is resulting in a growing need for datadriven 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 work-flow 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 service 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% for an eight-service workflow using
271 data products).},
added-at = {2014-08-13T04:08:36.000+0200},
author = {Simmhan, Yogesh L. and Plale, Beth and Gannon, Dennis},
biburl = {https://www.bibsonomy.org/bibtex/2c3fd9a537836d870058110308276c58c/simmhan},
doi = {10.4018/jwsr.2008040101},
interhash = {56afbf4d9a2d289f0f88eadd2377c62a},
intrahash = {c3fd9a537836d870058110308276c58c},
issn = {1545-7362},
journal = {International Journal of Web Services Research (IJWSR)},
keywords = {escience, karma, msr, peer provenance, reviewed workflow,},
note = {[IF 0.371, CORE C]},
number = 2,
owner = {Simmhan},
pages = {1--22},
publisher = {IGI Publishing},
timestamp = {2014-08-13T04:08:36.000+0200},
title = {Karma2: Provenance Management for Data-Driven Workflows},
volume = 5,
year = 2008
}