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Issue No.06 - November/December (2009 vol.15)
pp: 1351-1358
Denis Gracanin , Virginia Tech., Blacksburg, USA
Kresimir Matkovic , VRVis Research Center, Vienna, Austria
Helwig Hauser , University of Bergen, Norway
ABSTRACT
The widespread use of computational simulation in science and engineering provides challenging research opportunities. Multiple independent variables are considered and large and complex data are computed, especially in the case of multi-run simulation. Classical visualization techniques deal well with 2D or 3D data and also with time-dependent data. Additional independent dimensions, however, provide interesting new challenges. We present an advanced visual analysis approach that enables a thorough investigation of families of data surfaces, i.e., datasets, with respect to pairs of independent dimensions. While it is almost trivial to visualize one such data surface, the visual exploration and analysis of many such data surfaces is a grand challenge, stressing the users’ perception and cognition. We propose an approach that integrates projections and aggregations of the data surfaces at different levels (one scalar aggregate per surface, a 1D profile per surface, or the surface as such). We demonstrate the necessity for a flexible visual analysis system that integrates many different (linked) views for making sense of this highly complex data. To demonstrate its usefulness, we exemplify our approach in the context of a meteorological multi-run simulation data case and in the context of the engineering domain, where our collaborators are working with the simulation of elastohydrodynamic (EHD) lubrication bearing in the automotive industry.
INDEX TERMS
interactive visual analysis, family of surfaces, coordinated multiple views, multidimensional multivariate data
CITATION
Denis Gracanin, Kresimir Matkovic, Helwig Hauser, "Interactive Visual Analysis of Complex Scientific Data as Families of Data Surfaces", IEEE Transactions on Visualization & Computer Graphics, vol.15, no. 6, pp. 1351-1358, November/December 2009, doi:10.1109/TVCG.2009.155
REFERENCES
[1] W. Aigner, S. Miksch, W. Müller, H. Schumann, and C. Tominski, Visual methods for analyzing time-oriented data. IEEE Transactions on Visualization and Computer Graphics, 14 (1): 47–60, 2008.
[2] E. Bauer and A. Ganopolski, Simulation of the cold climate event 8200 years ago by meltwater outburst from Lake Agassiz. Paleoceanography, 19(PA3014): 1–13, 2004.
[3] R. Bürger and H. Hauser, Visualization of multi-variate scientific data. In EuroGraphics State of the Art Reports (STARs), pages 117–134, 2007.
[4] J. V. Carlis and J. A. Konstan, Interactive visualization of serial periodic data. In UIST '98: Proceedings of the 11th Annual ACM Symposium on User Interface Software and Technology, pages 29–38. ACM Press, 1998.
[5] H. Doleisch, M. Gasser, and H. Hauser, Interactive feature specification for focus+context visualization of complex simulation data. In G.-P. Bonneau, S. Hahmann, and C. D. Hansen editors, Proc. of the Joint EUROGRAPHICS - IEEE TCVG Symp. on Vis., 2003.
[6] B. Francis, and J. Pritchard, Visualisation of historical events using Lexis pencils. Advisory Group on Computer Graphics, 1997.
[7] H. Hauser, Generalizing Focus+Context Visualization, in Scientific Visualization: The Visual Extraction of Knowledge from Data, chapter Generalizing Focus+Context Visualization, pages 305–327. Springer, 2006.
[8] S. Havre, E. Hetzler, P. Whitney, and L. Nowell, ThemeRiver: Visualizing thematic changes in large documents collections. IEEE Transactions on Visualization and Computer Graphics, 8 (1): 9–20, 2002.
[9] H. Hochheiser and B. Shneiderman, Dynamic query tools for time series data sets: timebox widgets for interactive exploration. Information Visualization, 3 (1): 1–18, 2004.
[10] D. H. House, A. S. Bair, and C. Ware, An approach to the perceptual optimization of complex visualizations. IEEE Transactions on Visualization and Computer Graphics, 12 (4): 509–521, 2006.
[11] D. A. Keim, Visual exploration of large data sets. Communications of the ACM, 44 (8): 38–44, Aug. 2001.
[12] Z. Konyha, K. Matković, D. Gračanin, M. Jelović, and H. Hauser, Interactive visual analysis of families of function graphs. IEEE Transactions on Visualization and Computer Graphics, 12 (6): 1373–1385, 2006.
[13] M. Levoy, Display of surfaces from volume data. IEEE Computer Graphics and Applications, 8 (3): 29–37, 1988.
[14] K. Matkovic, D. Gracanin, M. Jelovic, and H. Hauser, Interactive visual steering - rapid visual prototyping of a common rail injection system. IEEE Transactions on Visualization and Computer Graphics, 14 (6): 1699–1706, 2008.
[15] M. Monmonier, Strategies for the visualization of geographic time-series data. Cartographica, 27 (1): 30–45, 1990.
[16] M. Novotný and H. Hauser, Outlier-preserving focus+context visualization in parallel coordinates. IEEE Transactions on Visualization and Computer Graphics, 12 (5): 893–900, 2006.
[17] G. Offner, Quality and Validation of Cranktrain Vibration Prediction - Effect of Hydrodynamic Journal Bearing Models. In Multi-body Dynamics - Monitoring and Simulation Techniques III, 2004.
[18] H. H. Priebsch and J. Krasser, Simulation of Vibration and Structure Borne Noise of Engines - A Combined Technique of FEM and Multi Body Dynamics. 1998.
[19] J. C. Roberts, State of the Art: Coordinated & Multiple Views in Exploratory Visualization. In G. Andrienko, J. C. Roberts, and C. Weaver editors, Proc. of the 5th International Conference on Coordinated & Multiple Views in Exploratory Visualization. IEEE CS Press, 2007.
[20] E. R. Tufte, The Visual Display of Quantitive Information. Graphics Press, Cheshire, Connecticut, second edition, 2001.
[21] C. Ware, Information Visualization: Perception for Design. Morgan Kaufmann Publishers, second edition, 2004.
[22] M. Weber, M. Alexa, and W. Müller, Visualizing time-series on spirals. In Proc. of the IEEE Symp. on Information Visualization, pages 7–13, 2001.
[23] R. Wegenkittl, H. Löffelmann, and E. Gröller, Visualizing the behavior of higher dimensional dynamical systems. In Proceedings of the IEEE Visualization (VIS '97), pages 119–125, 1997.
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