CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
A spreadsheet approach to information visualization
Proceedings of the 10th annual ACM symposium on User interface software and technology
Introduction to data visualization
Information visualization in data mining and knowledge discovery
IEEE Transactions on Visualization and Computer Graphics
Polaris: A System for Query, Analysis, and Visualization of Multidimensional Relational Databases
IEEE Transactions on Visualization and Computer Graphics
Towards Ubiquitous Brushing for Information Visualization
IV '06 Proceedings of the conference on Information Visualization
Exploring OLAP aggregates with hierarchical visualization techniques
Proceedings of the 2007 ACM symposium on Applied computing
XmdvtoolQ:: quality-aware interactive data exploration
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
State of the Art: Coordinated & Multiple Views in Exploratory Visualization
CMV '07 Proceedings of the Fifth International Conference on Coordinated and Multiple Views in Exploratory Visualization
A Taxonomy of Clutter Reduction for Information Visualisation
IEEE Transactions on Visualization and Computer Graphics
Interactive and Dynamic Graphics for Data Analysis With R and GGobi
Interactive and Dynamic Graphics for Data Analysis With R and GGobi
IEEE Transactions on Visualization and Computer Graphics
Cross-Filtered Views for Multidimensional Visual Analysis
IEEE Transactions on Visualization and Computer Graphics
Flexible Linked Axes for Multivariate Data Visualization
IEEE Transactions on Visualization and Computer Graphics
Brushing Dimensions—A Dual Visual Analysis Model for High-Dimensional Data
IEEE Transactions on Visualization and Computer Graphics
Visualization tree, multiple linked analytical decisions
SG'05 Proceedings of the 5th international conference on Smart Graphics
Improving Visualization of Large Hierarchical Clustering
IV '12 Proceedings of the 2012 16th International Conference on Information Visualisation
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Visualization techniques of all sorts suffer from visual cluttering, the occlusion of visual information due to the overlap of graphical items; and from excessive complexity in analytical tasks due to multiple parallel perspectives. To cope with these problems, we introduce Hierarchical Visual Filtering, a novel interaction principle based on pragmatic and epistemic actions. Pragmatic actions here mean that the analyst is able to visually select and filter information, determining visual configurations that reveal different perspectives; epistemic actions mean that the analyst can record, annotate, and recall intermediate visualizations created pragmatically. To do so, we use a tree-like organization to keep multiple visualization workspaces linked according to the analytical decisions took by the user. Our goal is to promote an innovative systematization that can augment the potential for database visual inspection, and for visualization systems in general. It is our contention that Hierarchical Visual Filtering can inspire a novel scheme of visualization environments in which space limitations and complexity are treated by means of interactive tasks.