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22nd International Conference on Data Engineering Workshops (ICDEW'06)
Towards a Quality Model for Effective Data Selection in Collaboratories
Atlanta, Georgia
April 03-April 07
ISBN: 0-7695-2571-7
ASCII Text
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Yogesh L. Simmhan, Beth Plale, Dennis Gannon, "Towards a Quality Model for Effective Data Selection in Collaboratories," Data Engineering Workshops, 22nd International Conference on, pp. 72, 22nd International Conference on Data Engineering Workshops (ICDEW'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICDEW.2006.150,
author = {Yogesh L. Simmhan and Beth Plale and Dennis Gannon},
title = {Towards a Quality Model for Effective Data Selection in Collaboratories},
journal ={Data Engineering Workshops, 22nd International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2571-7},
pages = {72},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDEW.2006.150},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Engineering Workshops, 22nd International Conference on
TI - Towards a Quality Model for Effective Data Selection in Collaboratories
SN - 0-7695-2571-7
SP
EP
A1 - Yogesh L. Simmhan,
A1 - Beth Plale,
A1 - Dennis Gannon,
PY - 2006
KW - null
VL - 0
JA - Data Engineering Workshops, 22nd International Conference on
ER -
 
Yogesh L. Simmhan, Indiana University
Beth Plale, Indiana University
Dennis Gannon, Indiana University
Data-driven scientific applications utilize workflow frameworks to execute complex dataflows, resulting in derived data products of unknown quality. We discuss our on-going research on a quality model that provides users with an integrated estimate of the data quality that is tuned to their application needs and is available as a numerical quality score that enables uniform comparison of datasets, providing a way for the community to trust derived data.
Citation:
Yogesh L. Simmhan, Beth Plale, Dennis Gannon, "Towards a Quality Model for Effective Data Selection in Collaboratories," icdew, pp.72, 22nd International Conference on Data Engineering Workshops (ICDEW'06), 2006
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