30 Years of Multidimensional Multivariate Visualization
Scientific Visualization, Overviews, Methodologies, and Techniques
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Uncovering Clusters in Crowded Parallel Coordinates Visualizations
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Low-Level Components of Analytic Activity in Information Visualization
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
Visual Analysis of the Air Pollution Problem in Hong Kong
IEEE Transactions on Visualization and Computer Graphics
Scattering Points in Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
Judging correlation from scatterplots and parallel coordinate plots
Information Visualization
IEEE Transactions on Visualization and Computer Graphics
Evaluation of Parallel Coordinates for Interactive Alarm Filtering
IV '11 Proceedings of the 2011 15th International Conference on Information Visualisation
Flexible Linked Axes for Multivariate Data Visualization
IEEE Transactions on Visualization and Computer Graphics
A knowledge integration framework for information visualization
From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments
Evaluation of cluster identification performance for different PCP variants
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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One of the fundamental tasks for analytic activity is retrieving (i.e., reading) the value of a particular quantity in an information visualization. However, few previous studies have compared user performance in such value retrieval tasks for different visualizations. We present an experimental comparison of user performance (time and error distance) across four multivariate data visualizations. Three variants of scatterplot (SCP) visualizations, namely SCPs with common vertical axes (SCP-common), SCPs with a staircase layout (SCP-staircase), and SCPs with rotated axes between neighboring cells (SCP-rotated), and a baseline parallel coordinate plots (PCP) were compared. Results show that the baseline PCP is better than SCP-rotated and SCP-staircase under all conditions, while the difference between SCP-common and PCP depends on the dimensionality and density of the dataset. PCP shows advantages over SCP-common when the dimensionality and density of the dataset are low, but SCP-common eventually outperforms PCP as data dimensionality and density increase. The results suggest guidelines for the use of SCPs and PCPs that can benefit future researchers and practitioners. © 2012 Wiley Periodicals, Inc.