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A Taxonomy of Clutter Reduction for Information Visualisation
November/December 2007 (vol. 13 no. 6)
pp. 1216-1223
ASCII Text
x 
 
Geoffrey Ellis, Alan Dix, "A Taxonomy of Clutter Reduction for Information Visualisation," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1216-1223, November/December, 2007.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2007.70535,
author = {Geoffrey Ellis and Alan Dix},
title = {A Taxonomy of Clutter Reduction for Information Visualisation},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {13},
number = {6},
issn = {1077-2626},
year = {2007},
pages = {1216-1223},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2007.70535},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - A Taxonomy of Clutter Reduction for Information Visualisation
IS - 6
SN - 1077-2626
SP1216
EP1223
EPD - 1216-1223
A1 - Geoffrey Ellis,
A1 - Alan Dix,
PY - 2007
KW - Clutter reduction
KW - information visualisation
KW - occlusion
KW - large datasets
KW - taxonomy.
VL - 13
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Information visualisation is about gaining insight into data through a visual representation. This data is often multivariate and increasingly, the datasets are very large. To help us explore all this data, numerous visualisation applications, both commercial and research prototypes, have been designed using a variety of techniques and algorithms. Whether they are dedicated to geo-spatial data or skewed hierarchical data, most of the visualisations need to adopt strategies for dealing with overcrowded displays, brought about by too much data to fit in too small a display space. This paper analyses a large number of these clutter reduction methods, classifying them both in terms of how they deal with clutter reduction and more importantly, in terms of the benefits and losses. The aim of the resulting taxonomy is to act as a guide to match techniques to problems where different criteria may have different importance, and more importantly as a means to critique and hence develop existing and new techniques.

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Index Terms:
Clutter reduction, information visualisation, occlusion, large datasets, taxonomy.
Citation:
Geoffrey Ellis, Alan Dix, "A Taxonomy of Clutter Reduction for Information Visualisation," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1216-1223, Nov.-Dec. 2007, doi:10.1109/TVCG.2007.70535
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