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
Introduction to data visualization
Information visualization in data mining and knowledge discovery
Visualizing multi-dimensional clusters, trends, and outliers using star coordinates
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
XmdvTool: visual interactive data exploration and trend discovery of high-dimensional data sets
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Knowledge Discovery in Databases
Knowledge Discovery in Databases
Information Visualization and Visual Data Mining
IEEE Transactions on Visualization and Computer Graphics
VisDB: Database Exploration Using Multidimensional Visualization
IEEE Computer Graphics and Applications
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
High Dimensional Brushing for Interactive Exploration of Multivariate Data
VIS '95 Proceedings of the 6th conference on Visualization '95
Interactive Information Visualization of a Million Items
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Parallel coordinates: a tool for visualizing multi-dimensional geometry
VIS '90 Proceedings of the 1st conference on Visualization '90
Hierarchical visual filtering, pragmatic and epistemic actions for database visualization
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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In this paper we tackle the main problem presented by the majority of Information Visualization techniques, that is, the limited number of data items that can be visualized simultaneously. Our approach proposes an innovative and interactive systematization that can augment the potential for data presentation by utilizing multiple views. These multiple presentation views are kept linked according to the analytical decisions took by the user and are tracked in a tree-like structure. Our emphasis is on developing an intuitive yet powerful system that helps the user to browse the information and to make decisions based both on overview and on detailed perspectives of the data under analysis. The visualization tree keeps track of the interactive actions taken by the user without losing context.