An evaluation of pan & zoom and rubber sheet navigation with and without an overview
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PRISAD: a partitioned rendering infrastructure for scalable accordion drawing (extended version)
Information Visualization
Composite Rectilinear Deformation for Stretch and Squish Navigation
IEEE Transactions on Visualization and Computer Graphics
ASK-GraphView: A Large Scale Graph Visualization System
IEEE Transactions on Visualization and Computer Graphics
Combining extended table lens and treemap techniques for visualizing tabular data
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
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We present PRISAD, the first generic rendering infrastructure for information visualization applications that use the accordion drawing technique: rubber-sheet navigation with guaranteed visibility for marked areas of interest. Our new rendering algorithms are based on the partitioning of screen-space, which allows us to handle dense dataset regions correctly. The algorithms in previous work led to incorrect visual representations because of overculling, and to inefficiencies due to overdrawing multiple items in the same region. Our pixel-based drawing infrastructure guarantees correctness by eliminating overculling, and improves rendering performance with tight bounds on overdrawing. PRITree and PRISeq are applications built on PRISAD, with the feature sets of TreeJuxtaposer and SequenceJuxtaposer, respectively. We describe our PRITree and PRISeq dataset traversal algorithms, which are used for efficient rendering, culling, and layout of datasets within the PRISAD framework. We also discuss PRITree node marking techniques, which offer order-of-magnitude improvements to both memory and time performance versus previous range storage and retrieval techniques. Our PRITree implementation features a five-fold increase in rendering speed for non-trivial tree structures, and also reduces memory requirements in some realworld datasets by up to eight times, so we are able to handle trees of several million nodes. PRISeq renders fifteen times faster and handles datasets twenty times larger than previous work.