Data Quality Evaluation of Scientific Datasets - A Case Study in a Policy Support Context

In this work we present the rule-based approach used to evaluate the qu ality of scientific datasets in a policy support context. The used case study refers to real datasets in a conte xt where low data quality limits the accuracy of the analysis results and, consequently, the significance of th provided policy advice. The applied solution consists in the identification of types of constraints that can be usefu l as data quality rules and in the development of a software tool to evaluate a dataset on the basis of a s et of rules expressed in the XML markup language. As rule types we selected some types of data constrain ts and dependencies already proposed in data quality works, but we experimented also the use of order depende ncies and existence constraints. The case study was used to develop and test the adopted solution, which is anyw ay generally applicable to other