Towards a Quality Model for Effective Data Selection in Collaboratories

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.

• Type: Conference
• Year: 2006
• Where: ICDE
• Authors: Yogesh Simmhan, Beth Plale, Dennis Gannon
• Keywords: Applications Utilize Workflow, Database, ICDE 2006, Numerical Quality Score, Unknown Quality