Data Quality Analysis for Food Composition Databases
A Toolkit for Measuring and Visualising Data Quality
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Data quality has already been an issue even before databases were invented. Despite the absence of a clear definition, it is widely agreed that data quality is of major importance especially in scientific applications. It is all the more surprising how little research has been done in the area of data quality. We present a Data Quality Analysis Toolkit which is capable of measuring and visualising data quality. A variety of different charts and tables support the user in judging in what area urgent action is needed. Furthermore, the toolkit provides tools to drill down on the data quality issu...
Data quality has already been an issue even before databases were invented. Despite the absence of a clear definition, it is widely agreed that data quality is of major importance especially in scientific applications. It is all the more surprising how little research has been done in the area of data quality. We present a Data Quality Analysis Toolkit which is capable of measuring and visualising data quality. A variety of different charts and tables support the user in judging in what area urgent action is needed. Furthermore, the toolkit provides tools to drill down on the data quality issues and identify individual problems in the data. In this master thesis we apply our concept of data quality analysis to the FoodCASE database, which is the Swiss food composition database managed by the Swiss Food Information Resource (SwissFIR) of the ETH Zurich and the Federal Office of Public Health.
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