Pixel-Oriented Visualization Techniques for Exploring Very Large Data Bases
Daniel A. Keim · Journal of Computational and Graphical Statistics · 1996
An important goal of visualization technology is to support the exploration and analysis of very large amounts of data. This article describes a set of pixel-oriented visualization techniques that use each pixel of the display to visualize one data value and therefore allow the visualization of the largest amount of data possible. Most of the techniques have been specifically designed for visualizing and querying large data bases. The techniques may be divided into query-independent techniques that directly visualize the data (or a certain portion of it) and query-dependent techniques that visualize the data in the context of a specific query. Examples for the class of query-independent techniques are the screen-filling curve and recursive pattern techniques. The screen-filling curve techniques are based on the well-known Morton and Peano–Hilbert curve algorithms, and the recursive pattern technique is based on a generic recursive scheme, which generalizes a wide range of pixel-oriented arrangements for visualizing large data sets. Examples for the class of query-dependent techniques are the snake-spiral and snake-axes techniques, which visualize the distances with respect to a data base query and arrange the most relevant data items in the center of the display. In addition to describing the basic ideas of our techniques, we provide example visualizations generated by the various techniques, which demonstrate the usefulness of our techniques and show some of their advantages and disadvantages.