Constraint Simplification for Data Editing of Numerical Variables

Abstract

Data editing is the process of checking and correcting data. In practise, these processes are often automated. A large number of constraints needs to be handled in many applications. This article shows that data editing can benefit from automated constraint simplification techniques. Performance can be improved, which broadens the scope of applicability of automatic data editing. Flaws in edit rule formulation may be detected, which improves the quality of automatic edited data.