Investigating a Constraint-Based Approach to Data Quality in Information Systems

Constraints are tightly coupled with data validation and data quality. The author investigates in this master thesis to what extent constraints can be used to build a data quality management framework that can be used by an application developer to control the data quality of an information system. The conceptual background regarding the definition of data quality and its multidimensional concept followed by a constraint type overview is presented in detail. Moreover, the results of a broad research for existing concepts and technical solutions regarding constraint definition and data validation with a strong focus on the Java programming language environment are explained. Based on these insights, we introduce a data quality management framework implementation based on the Java Specification Request (JSR) 349 (Bean Validation 1.1) using a single constraint model which avoids inconsistencies and redundancy within the constraint specification and validation process. This data quality management framework contains advanced constraints like an association constraint which restricts the cardinalities between entities in a dynamic way and the concept of temporal constrains which allows that a constraint must only hold at a certain point in time. Furthermore, a time-triggered validation component implementation which allows the scheduling of validation jobs is described. The concept of hard and soft constraints is explained in detail and supplemented with a implementation suggestion using Bean Validation. Moreover, we explain how constraints could be used to increase the data quality. A demonstrator application shows the utilisation of the data quality management framework.