Oh, That's What You Meant! The Interplay of Data Quality and Data Semantics Stuart Madnick   View Paper (PDF)   Return to Keynote Speakers Abstract Data quality issues have taken on increasing importance in recent years. In our research, we have discovered that many data quality problems are actually data misinterpretation problems – that is, problems with data semantics. In this paper, we first illustrate some examples of these problems and then introduce a particular semantic problem that we call corporate householding. We stress the importance of context to get the appropriate answer for each task. Then we propose an approach to handle these tasks using extensions to the COntext INterchange (COIN) technology for knowledge storage and knowledge processing. ©2005 Association for Computing Machinery