Abstract
Last two decades have seen the development of varieties of new methods for visualizing multivariable data and a few attempts have been made to survey and compare some of these techniques. Despite valuable reviews, they did not systematically study the perception tasks involved in these techniques which affect the efficiency of their information decoding due to limited humans’ visual perception system. This paper serves to fill this gap through reviewing three well known multivariate visualization techniques apropos their associated perception tasks for three data exploration purposes. Advantages and disadvantages of each tool are discussed.
Chapter PDF
References
Cleveland, W.S.: Visualizing Data. Hobart Press, New Jersey (1993)
Wong, P.C., Bergeron, D.: 30 Years of Multidimensional Multivariate Visualization. In: Nielson, G., Hagan, H., Muller, H. (eds.) Scientific Visualization – Overview, Methodologies, and Techniques, pp. 3–33. IEEE Computer Society Press, Los Alamitos (1997)
Tatu, A., Albuquerque, G., Eisemann, M., Schneidewind, J., Theisel, H., Magnork, M., Keim, D.: Combining Automated Analysis and Visualization Techniques for Effective Exploration of High-Dimensional Data. In: 2009 IEEE Symposium on Visual Analytics Science and Technology, pp. 59–66 (2009)
Keim, D.A.: Information Visualization and Visual Data Mining. IEEE Transactions on Visualization and Computer Graphics 8(1), 1–8 (2002)
Keim, D.A., Kriegel, H.-P.: Visualization Techniques for Mining Large Databases: A Comparison. IEEE Transactions on Knowledge and Data Engineering, Special Issue on Data Mining 8(6), 1–29 (1996)
Grinstein, G., Patrick, E., Pickett, R.M., Laskowski, S.J.: Benchmark Development for the Evaluation of Visualization for Data Mining. In: UsFayyad, U., Grinstein, G., Wierse, A. (eds.) Information Visualization in Data Mining and Knowledge Discovery, pp. 129–176. Morgan Kaufmann Publishers, San Francisco (2002)
UCI Machine Learning Repository Irvine, CA: University of California, School of Information and Computer Science, http://archive.ics.uci.edu/ml
Cleveland, W.S., McGill, R.: Graphical Perception: The Visual Decoding of Quantitative Information on Statistical Graphs (with Discussion). Journal of the Royal Statistical Society Series A 150(3), 192–229 (1987)
Inselberg, A.: The Plane with Parallel Coordinates. The Visual Computer 1(1), 69–97 (1985)
Keim, D.A.: Designing Pixel-Oriented Visualization Techniques: Theory and Applications. IEEE Transactions on Visualization and Computer Graphics 6(1), 59–78 (2002)
Hao, M.C., Dayal, U., Keim, D., Schreck, T.A.: Visual Analysis of Multi-Attribute Data Using Pixel Matrix Displays. In: Proceedings of the SPIE - The International Society for Optical Engineering Visualization and Data Analysis, vol. 6495, p. 649505-1-9 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, Y. (2011). Multivariate Data Visualization: A Review from the Perception Aspect. In: Smith, M.J., Salvendy, G. (eds) Human Interface and the Management of Information. Interacting with Information. Human Interface 2011. Lecture Notes in Computer Science, vol 6771. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21793-7_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-21793-7_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21792-0
Online ISBN: 978-3-642-21793-7
eBook Packages: Computer ScienceComputer Science (R0)