VisDB: Database Exploration Using Multidimensional Visualization
IEEE Computer Graphics and Applications
Supporting Data Mining of Large Databases by Visual Feedback Queries
Proceedings of the Tenth International Conference on Data Engineering
Parallel coordinates: a tool for visualizing multi-dimensional geometry
VIS '90 Proceedings of the 1st conference on Visualization '90
Pixel-oriented database visualizations
ACM SIGMOD Record
Displaying data in multidimensional relevance space with 2D visualization maps
VIS '97 Proceedings of the 8th conference on Visualization '97
Proceedings of the conference on Visualization '98
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
Towards a Novel OLAP Interface for Distributed Data Warehouses
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Immersed Visual Data Mining: Walking the Walk
BNCOD 18 Proceedings of the 18th British National Conference on Databases: Advances in Databases
Similarity Clustering of Dimensions for an Enhanced Visualization of Multidimensional Data
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
Case studies: Public domain, single mining tasks systems: VisDB
Handbook of data mining and knowledge discovery
3D visual data mining: goals and experiences
Computational Statistics & Data Analysis - Data visualization
Journal of Parallel and Distributed Computing
VIEW'06 Proceedings of the 1st first visual information expert conference on Pixelization paradigm
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The VisDB system developed at the University of Munich is a sophisticated tool for visualizing and analyzing large databases. The key idea of the VisDB system is to support the exploration of large databases by using the phenomenal abilities of the human vision system which is able to analyze visualizations of mid-size to large amounts of data very efficiently. The goal of the VisDB system is to provide visualizations of large portions of the database, allowing properties of the data and structure in the data to become perceptually apparent.