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Guest Editorial for the Special Issue on Data Quality in Databases

Interdisciplinary research addressing the challenges of information quality touches a diversity of topics including economics, psychology, information systems, data mining, database technology, and many others. Venues such as this ACM Journal for Data and Information Quality (JDIQ), the annual International Conference on Information Quality (ICIQ), and the annual QDB workshop strive to create opportunities to showcase research that bridge these disciplines and achieve a common goal, namely, to provide information of appropriately high quality for a multitude of different use cases and applications. While information systems research concentrates on the modeling of many facets and dimensions of information quality, computer science has a focus on the algorithmic and data management aspects of analyzing data with respect to diverse quality criteria and maintaining or increasing quality. This Special Issue on Data Quality in Databases highlights four of the latest computational and algorithmic results covering the following broad range of important data quality issues: