Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering

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Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering (2004)

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by Wei Peng , Matthew O. Ward , Elke A. Rundensteiner

Venue:	In INFOVIS ’04: Proceedings of the IEEE Symposium on Information Visualization (INFOVIS’04
Citations:	84 - 6 self

BibTeX

@INPROCEEDINGS{Peng04clutterreduction,
    author = {Wei Peng and Matthew O. Ward and Elke A. Rundensteiner},
    title = {Clutter Reduction in Multi-Dimensional Data Visualization Using Dimension Reordering},
    booktitle = {In INFOVIS ’04: Proceedings of the IEEE Symposium on Information Visualization (INFOVIS’04},
    year = {2004},
    pages = {89--96},
    publisher = {IEEE Computer Society}
}

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Abstract

Clutter denotes a disordered collection of graphical entities in information visualization. Clutter can obscure the structure present in the data. Even in a small dataset, clutter can make it hard for the viewer to find patterns and reveal relationships. In this paper, we present the concept of clutter-based dimension reordering. Our hope is to reduce clutter without reducing information content or disturb data in any way. Dimension order is a variable that can significantly affect a visualization's expressiveness. By varying the dimension order in visualizations, our goal is to find the views with the least amount of visual clutter. Clutter reduction is a display-dependent task. We define different measures of what constitutes clutter in terms of display properties for four different visualization techniques. We then apply dimension ordering algorithms to search for a order that minimizes the clutter in a display.

Keyphrases

clutter reduction dimension order information content structure present graphical entity disordered collection different visualization technique small dataset display-dependent task disturb data visual clutter different measure information visualization reveal relationship display property clutter-based dimension reordering

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