How not to lie with visualization
Computers in Physics
High-speed visual estimation using preattentive processing
ACM Transactions on Computer-Human Interaction (TOCHI)
Mapping semantic information in virtual space: dimensions, variance and individual differences
International Journal of Human-Computer Studies - Empirical evaluation of information visualizations
Evaluating the effectiveness of spatial memory in 2D and 3D physical and virtual environments
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visualization of bibliographic networks with a reshaped landscape metaphor
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
Empirical Study of a 3D Visualization for Information Retrieval Tasks
Journal of Intelligent Information Systems - Special issue: A survey of research questions for intelligent information systems in education
Visualizing the non-visual: spatial analysis and interaction with information from text documents
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Graphical Encoding for Information Visualization: An Empirical Study
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Spatial metaphors for browsing large data archives
Spatial metaphors for browsing large data archives
Information Visualization: Perception for Design
Information Visualization: Perception for Design
Analysis Experiences Using Information Visualization
IEEE Computer Graphics and Applications
Steerable, Progressive Multidimensional Scaling
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
The Distance-Similarity Metaphor in Region-Display Spatializations
IEEE Computer Graphics and Applications
Qualitative analysis of visualization: a building design field study
Proceedings of the 2008 Workshop on BEyond time and errors: novel evaLuation methods for Information Visualization
Quantifying the Path Preservation of SOM-Based Information Landscapes
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Quantitative data visualization with interactive KDE surfaces
Proceedings of the 26th Spring Conference on Computer Graphics
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
An assessment of email and spontaneous dialog visualizations
International Journal of Human-Computer Studies
EgoNav: exploring networks through egocentric spatializations
Proceedings of the International Working Conference on Advanced Visual Interfaces
Spatial autocorrelation-based information visualization evaluation
Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors - Novel Evaluation Methods for Visualization
The "Map" in the mental map: Experimental results in dynamic graph drawing
International Journal of Human-Computer Studies
Interfaces for discourse summarisation: a human factors analysis
Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
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Spatializations represent non-spatial data using a spatial layout similar to a map. We present an experiment comparing different visual representations of spatialized data, to determine which representations are best for a non-trivial search and point estimation task. Primarily, we compare point-based displays to 2D and 3D information landscapes. We also compare a colour (hue) scale to a grey (lightness) scale. For the task we studied, point-based spatializations were far superior to landscapes, and 2D landscapes were superior to 3D landscapes. Little or no benefit was found for redundantly encoding data using colour or greyscale combined with landscape height. 3D landscapes with no colour scale (height-only) were particularly slow and inaccurate. A colour scale was found to be better than a greyscale for all display types, but a greyscale was helpful compared to height-only. These results suggest that point-based spatializations should be chosen over landscape representations, at least for tasks involving only point data itself rather than derived information about the data space.