Data quality, which refers to correctness, uncertainty, completeness and other aspects of data, has became more and more prevalent and has been addressed across multiple disciplines. Data quality could be introduced and presented in any of the data manipulation processes such as data collection, transformation, and visualization. Data visualization is a process of data mining and analysis using graphical presentation and interpretation. The correctness and completeness of the visualization discoveries to a large extent depend on the quality of the original data. Without the integration of quality information with data presentation, the analysis of data using visualization is incomplete at best and can lead to inaccurate or incorrect conclusions at worst. This thesis addresses the issue of data quality visualization. Incorporating data quality measures into the data displays is challenging in that the display is apt to be cluttered when faced with multiple dimensions and data records. We investigate both the incorporation of data quality information in traditional multivariate data display techniques as well as develop novel visualization and interaction tools that operate in data quality space. We validate our results using several data sets that have variable quality associated with dimensions, records, and data values.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1065 |
| Date | 11 January 2005 |
| Creators | Huang, Shiping |
| Contributors | Michael A. Gennert, Department Head, Murali Mani, Reader, Matthew O. Ward, Advisor |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
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