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The DSL interpreter makes the data quality model executable therefore ensuring measurement and improving of data quality.
'The robustness of crop model results depends on data quality, model skill prediction and model complexity.
We feel that the option for the generic data quality model proposed by the ISO 25012 [ 30] standard is important to guarantee a domain independent perspective.
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In contradiction to traditional data quality assurance methods, the proposed approach provides the usage of a domain specific language (DSL) for description data quality models.
In this paper we have focused on three major aspects relating to quality aware query systems, namely measuring data quality, modeling of user׳s data quality preferences, and answering the query in consideration of the defined preferences and measures.
Problems with data quality and model specification can lead to incorrect projections.
Plots relating data quality with model quality using the Pearson correlation coefficient (CC) analysis described by Karplus and Diederichs (2012).
We could not exclude contribution of temporal change in disease prevalence and data quality to model performances.
Plots relating data quality with model quality at 4.0 Å-resolution) using the Pearson correlation coefficient (CC) analysis described by Karplus and Diederichs (2012).
Such automation would reduce the necessary and often tedious labor of model building, while at the same time guaranteeing that, for the available data, a quality model is reached.
By combining the strengths offered by these different modelling approaches, and taking spatial scale into consideration, our framework provides the means of overcoming common difficulties related to data quality and modelling techniques.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com