Display of Surfaces from Volume Data
IEEE Computer Graphics and Applications
Footprint evaluation for volume rendering
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Hierarchical splatting: a progressive refinement algorithm for volume rendering
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
A coherent projection approach for direct volume rendering
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
A rendering algorithm for visualizing 3D scalar fields
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Light reflection functions for simulation of clouds and dusty surfaces
SIGGRAPH '82 Proceedings of the 9th annual conference on Computer graphics and interactive techniques
High Dimensional Brushing for Interactive Exploration of Multivariate Data
VIS '95 Proceedings of the 6th conference on Visualization '95
IVEE: an Information Visualization and Exploration Environment
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Visualizing the non-visual: spatial analysis and interaction with information from text documents
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Dual multiresolution HyperSlice for multivariate data visualization
INFOVIS '96 Proceedings of the 1996 IEEE Symposium on Information Visualization (INFOVIS '96)
Texture splats for 3D scalar and vector field visualization
VIS '93 Proceedings of the 4th conference on Visualization '93
Interactive exploration of very large relational datasets through 3D dynamic projections
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
n23tool: a tool for exploring large relational datasets through 3D dynamic projections
Proceedings of the ninth international conference on Information and knowledge management
Business information visualization
Communications of the AIS
Case studies: Commercial, multiple mining tasks systems: mineSet
Handbook of data mining and knowledge discovery
Visualizing Association Rules for Text Mining
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Visualizing Sequential Patterns for Text Mining
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
Visual Exploration of Large Relational Data Sets through 3D Projections and Footprint Splatting
IEEE Transactions on Knowledge and Data Engineering
Give chance a chance: modeling density to enhance scatter plot quality through random data sampling
Information Visualization
Browsing large online data tables using generalized query previews
Information Systems
E-R Modeling and Visualization of Large Mutual Fund Data
Journal of Visualization
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
See what you know: analyzing data distribution to improve density map visualization
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
Volume visualization and visual queries for large high-dimensional datasets
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Improved sammon mapping method for visualization of multidimensional data
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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A method for efficiently volume rendering dense scatterplots of relational data is described. Plotting difficulties that arise from large numbers of data points, categorical variables, interaction with non-axis dimensions, and unknown values, are addressed by this method. The domain of the plot is voxelized using binning and then volume rendered. Since a table is used as the underlying data structure, no storage is wasted on regions with no data. The opacity of each voxel is a function of the number of data points in a corresponding bin. A voxel's color is derived by averaging the value of one of the variables for all the data points that fall in a bin. Other variables in the data may be mapped to external query sliders. A dragger object permits a user to select regions inside the volume.