Data quality management is a great challenge in today’s world due to increasing proliferation of abundant and heterogeneous datasets. All organizations that realize and maintain data intensive advanced applications should deal with data quality related problems on a daily basis. In these organization …

Dealing with data quality related problems is an important issue that all organizations face in realizing and sustaining data intensive advanced applications. Upon detecting these problems in datasets, data analysts often register them in issue tracking systems in order to address them later on categorically …

To gain insight into the success and possible bottlenecks in the criminal justice domain, good and trustworthy management information is required. This paper presents a case study of a data space system that facilitates the monitoring of data flows within as well as between organizations involved in …

Organizations face many challenges in maintaining the quality of data in their information systems. Often offline methods like surveys are used in existing data quality management solutions. These methods, which are usually used in infrequent time intervals, suffer from high costs, high delays, and low …

For the purpose of good and trustworthy management information for the government, our research institute has built a data space system that makes it possible to periodically monitor data flows within as well as between organizations of the justice domain. The aim of this system is to get insight into …

In this paper we present the concepts and implementation of a data space system for the management of data from heterogeneous sources in the criminal justice field. Our system exploits domain knowledge in the field of justice to streamline and to relate the content of different databases in the chain. …