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Data Quality

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 nine previous international workshops on the topic of Data and Information Quality, namely IQIS 2004-2006, CleanDB 2006 and QDB 2007-2011, 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.


The QDB 2012 Program is now available.:
Please click here to see the program.
Invited Speakers:
We are delighted to announce that we have two very interesting keynotes at this year edition of QDB workshop:

  • Professsor Erhard Rahm from University of Leipzig, Germany, will give a keynote about Scalable matching of real-world data. The talk will touch upon topics such as matching product offers from web sources and cloud-based entity matching.
  • Dr. Ihab Ilyas from Qatar Computing Research Institute will give a keynote about Non-destructive Cleaning: Modelling and Querying Possible Data Repairs.

  • Deadline Extension:
    Since we have received several requests for deadline extension, we decided to extend the deadline by one week (new deadline is June 6th, 2012 10:00PM PST). Please feel free to revise and polish your submission in this timeframe.

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