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

ZANZI Antonella;  TROMBETTA Alberto; 

2014-09-24

Institute for Systems and Technologies of Information, Control and Communication

JRC82447

http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004476401670174,    https://publications.jrc.ec.europa.eu/repository/handle/JRC82447,   

10.5220/0004476401670174,