The problem of poor data quality in databases, data warehousing and information systems largely and indistinctly affects every application domain.
Many data processing tasks (such as information integration, data sharing, information retrieval, and knowledge discovery from databases) require various forms of data preparation and consolidation with complex data processing techniques, because the data input to the algorithms is assumed to conform to nice data distributions, containing no missing, inconsistent or incorrect values. This leaves a large gap between the available "dirty" data and the available machinery to process the data for the application purposes.
Building on the established tradition of six previous international workshops on the topic of Data and Information Quality, namely IQIS 2004-2006, CleanDB 2006 and QDB 2007-2008, the Quality in Databases (QDB) workshop is a qualified forum for presenting and discussing novel ideas and solutions related to the problems of assessing, monitoring, improving, and maintaining the quality of data.