Workflows have evolved as the natural tool for scientists to model
their eScience experiments. With the scientific world producing data
at an explosive rate, workflows have an important part to play in
the end to end management of scientific data. To illustrate, workflow
can help with fault tolerance and ease of administration when ingesting
massive quantities of data using commodity hardware. The ability
for workflows to automatically collect provenance on derived scientific
data improves data discovery and publication capabilities. With better
support for interoperating with data centric tools, workflows can
become ubiquitous systems for scientific collaboration.
%0 Conference Paper
%1 Simmhan:swf:2008
%A Simmhan, Yogesh
%B International Workshop on Scientific Workflows (SWF)
%D 2008
%I IEEE
%K data escience, invited management, msr, workflows,
%P 472-473
%R 10.1109/SERVICES-1.2008.22
%T End-to-End Scientific Data Management Using Workflows
%X Workflows have evolved as the natural tool for scientists to model
their eScience experiments. With the scientific world producing data
at an explosive rate, workflows have an important part to play in
the end to end management of scientific data. To illustrate, workflow
can help with fault tolerance and ease of administration when ingesting
massive quantities of data using commodity hardware. The ability
for workflows to automatically collect provenance on derived scientific
data improves data discovery and publication capabilities. With better
support for interoperating with data centric tools, workflows can
become ubiquitous systems for scientific collaboration.
@inproceedings{Simmhan:swf:2008,
abstract = {Workflows have evolved as the natural tool for scientists to model
their eScience experiments. With the scientific world producing data
at an explosive rate, workflows have an important part to play in
the end to end management of scientific data. To illustrate, workflow
can help with fault tolerance and ease of administration when ingesting
massive quantities of data using commodity hardware. The ability
for workflows to automatically collect provenance on derived scientific
data improves data discovery and publication capabilities. With better
support for interoperating with data centric tools, workflows can
become ubiquitous systems for scientific collaboration.},
added-at = {2014-08-13T04:08:36.000+0200},
author = {Simmhan, Yogesh},
biburl = {https://www.bibsonomy.org/bibtex/23bd63757d49efc3df8ed4b3737aca17d/simmhan},
booktitle = {International Workshop on Scientific Workflows (SWF)},
doi = {10.1109/SERVICES-1.2008.22},
interhash = {9d18e6ab2a73573df6ec8136016560f3},
intrahash = {3bd63757d49efc3df8ed4b3737aca17d},
keywords = {data escience, invited management, msr, workflows,},
month = {July},
note = {Invited talk},
owner = {Simmhan},
pages = {472-473},
publisher = {IEEE},
series = {Congress on Services},
timestamp = {2014-08-13T04:08:36.000+0200},
title = {End-to-End Scientific Data Management Using Workflows},
year = 2008
}