Immersive Visual Data Mining: The 3DVDM Approach
A software system has been developed for the study of static and dynamic data visualization in the context of Visual Data Mining in Virtual Reality. We use a specific data set to illustrate how the visualization tools of the 3D Visual Data Mining (3DVDM) system can assist in detecting potentially interesting non-linear data relationships that are hard to discover using traditional statistical methods of analysis. These detected data structures can form a basis for specification of further explanatory statistical analysis. The visualization tools are shown to reveal many interesting patterns and in particular the dynamic data visualization appears to have a very promising potential.
To further explore the human faculties, sound has also been used to represent statistical data. Current technology enables us to create advanced real-time 3D soundscapes which may prove useful since the human ears’ field of hearing is larger than the eyes’ field of view, and thus is able to inform us on events happening in areas that we cannot see. The audio-visual tools in the 3DVDM system are tested and the effectiveness of them is discussed for situations where sound acts as support for visual exploration, as well as use of sound as a sole cue for analyzing data in VR.
KeywordsVirtual Reality Virtual World Visual Object Color Scale Distance Threshold
Unable to display preview. Download preview PDF.
- 2.Inselberg, A., Dimsdale, B.: Parallel coordinates: a tool for visualizing multi-dimensional geometry. In: VIS 1990: Proceedings of the 1st conference on Visualization 1990, pp. 361–378. IEEE Computer Society Press, Los Alamitos (1990)Google Scholar
- 3.Nelson, L., Cook, D., Cruz-Neira, C.: Xgobi vs the c2: Results of an experiment comparing data visualization in a 3-d immersive virtual reality environment with a 2-d workstation display. Computational Statistics: Special Issue on Interactive Graphical Data Analysis 14, 39–51 (1999)zbMATHGoogle Scholar
- 4.Nagel, H.R., Granum, E., Musaeus, P.: Methods for visual mining of data in virtual reality. In: Proceedings of the International Workshop on Visual Data Mining, in conjunction with ECML/PKDD2001, Freiburg, Germany, 2nd European Conference on Machine Learning and 5th European Conference on Principles and Practice of Knowledge Discovery in Databases, September 2001, pp. 13–28 (2001)Google Scholar
- 5.Nagel, H.R.: Exploratory Visual Data Mining in Spatio-Temporal Virtual Reality. PhD dissertation, Faculty of Engineering and Science. Aalborg University. Denmark (2005)Google Scholar
- 6.Granum, E., Musaeus, P.: Constructing virtual environments for visual explorers. In: Quotrup, L. (ed.) Virtual Space: The Spatiality of Virtual Inhabited 3D Worlds, Springer, Heidelberg (2002)Google Scholar
- 7.Symanzik, J., Cook, D., Kohlmeyer, B.D., Lechner, U., Cruz-Neira, C.: Dynamic statistical graphics in the c2 virtual environment. In: Second World Conference of the International Association for Statistical Computing, Pasadena, California, USA, February 1997, vol. 29, pp. 35–40 (1997)Google Scholar
- 9.Carr, D.B., Nicholson, W.L.: Evaluation of graphical techniques for data in dimensions 3 to 5: Scatterplot matrix, glyph, and stereo examples. In: Proceedings of the Section on Statistical Computing, Alexandria, VA, American Statistical Association, pp. 229–235 (1985)Google Scholar
- 10.Pickett, R.M., Grinstein, G.: Iconographic displays for visualizing multidimensional data. In: Proceedings of the IEEE Conference on Systems, Beijing and Shenyang, People’s Republic of China, Man and Cybernetics, pp. 514–519 (1988)Google Scholar
- 11.Ribarsky, W., Ayers, E., Eble, J., Mukherjea, S.: Glyphmaker: Creating customized visualizations of complex data, pp. 57–64. IEEE Computer, Los Alamitos (July 1994)Google Scholar
- 14.Ebert, D.S., Rohrer, R.M., Shaw, C.D., Panda, P., Kukla, J.M., Roberts, D.A.: Procedural shape generation for multi-dimensional data visualization. In: Gröller, E., Löffelmann, H., Ribarsky, W. (eds.) Data Visualization 1999, pp. 3–12. Springer, Wien (1999)Google Scholar
- 15.Brown, M.L., Newsome, S.L., Glinert, E.P.: An experiment into the use of auditory cues to reduce visual workload. In: CHI 1989 Proceedings, New York, USA (1989)Google Scholar
- 16.Mutanen, J.: Perception of sound source distance, Nokia Research Center (2003)Google Scholar
- 17.Baluert, J.: Spatial hearing: the psychophysics of human sound localization. The MIT Press, Cambridge (1997)Google Scholar
- 18.Nagel, H.R., Granum, E.: Vr++ and its application for interactive and dynamic visualization of data in virtual reality. In: Proceedings of the Eleventh Danish Conference on Pattern Recognition and Image Analysis, Copenhagen, Denmark (August 2002)Google Scholar
- 19.Nagel, H.R., Granum, E.: A software system for temporal data visualization in virtual reality. In: Proceedings of the Workshop on Data Visualization for large data sets and Data Mining, Augsburg, Germany, Department of Computer Oriented Statistics and Data Analysis University of Augsburg (October 2002)Google Scholar
- 20.Zahorik, P.: Auditory display of sound source distance. In: Proceedings of the 2002 International Conference on Auditory Displays, Kyoto, Japan (July 2002)Google Scholar
- 21.Blackard, J.A.: Comparison of Neural Networks and Discriminant Analysis in Predicting Forest Cover Types. PhD dissertation, Department of Forest Sciences. Colorado State University. Fort Collins, Colorado (1998)Google Scholar
- 23.Cundy, H., Rollett, A.: Mathematical Models, 3rd edn. Tarquin Pub., Stradbroke (1989)Google Scholar
- 24.Gray, A.: Modern Differential Geometry of Curves and Surfaces with Mathematica, 2nd edn. CRC Press, Boca Raton (1997)Google Scholar