Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
Information visualization: perception for design
Information visualization: perception for design
The Information Mural: A Technique for Displaying and Navigating Large Information Spaces
IEEE Transactions on Visualization and Computer Graphics
Designing Pixel-Oriented Visualization Techniques: Theory and Applications
IEEE Transactions on Visualization and Computer Graphics
Visual hierarchical dimension reduction for exploration of high dimensional datasets
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
Dual multiresolution HyperSlice for multivariate data visualization
INFOVIS '96 Proceedings of the 1996 IEEE Symposium on Information Visualization (INFOVIS '96)
Interactive Information Visualization of a Million Items
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
CircleView: a new approach for visualizing time-related multidimensional data sets
Proceedings of the working conference on Advanced visual interfaces
Physical navigation to support graph exploration on a large high-resolution display
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Proceedings of the 3rd BELIV'10 Workshop: BEyond time and errors: novel evaLuation methods for Information Visualization
Visual boosting in pixel-based visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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Pixel-based visualization techniques have proven to be of high value in visual data exploration, since mapping data points to pixels not only allows the analysis and visualization of large data sets, but also provides an intuitive way to convert raw data into a graphical form that often fosters new insights, encouraging the formation and validation of new hypotheses to the end of better problem solving and gaining deeper domain knowledge. But the ever increasing mass of information leads to new challenges on pixel-based techniques and concepts, since the volume, complexity and dynamic nature of today's scientific and commercial data sets are beyond the capability of many of current presentation techniques. Most existing pixel based approaches do not scale well on such large data sets as visual representation suffers from the high number of relevant data points, that might be even higher than the available monitor resolution and does therefore not allow a direct mapping of all data points to pixels on the display. In this paper we focuses on ways to increase the scalability of pixel based approaches by integrating relevance driven techniques into the visualization process. We provide first examples for effective scalable pixel based visualizations of financial- and geo-spatial data.