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

In: International Conference on Data Engineering Workshops (ICDEW) – Scientific Workflows and Dataflows (SciFlow)

Publisher: IEEE Computer Society

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