Abstract
Understanding air quality data is important for many environmental and climatic applications that are crucial to our daily life. It is often challenging to handle these 3D datasets due to their large number of time steps and multiple interactional chemicals. In this paper, we design and generate knowledge templates for visually analyzing multi-field, time-varying 3D air quality data. Specifically, we design a set of multi-level knowledge templates to capture important statistical data properties based on the distribution features of air quality data. We develop a fast template synthesis method to generate suitable templates according to user intentions. We have also developed an integrated visualization system for visually comparing multiple templates and volume datasets. Our approach can automatically synthesize suitable knowledge templates to assist the visualization and analysis tasks of multiple related datasets. The experimental results demonstrate that appropriate knowledge templates can significantly improve the exploration and analysis processes of air quality data by encapsulating long-time range knowledge into understandable visual formats.
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References
Burkhard, R.: Learning from architects: the difference between knowledge visualization and information visualization. In: Eighth International Conference on Information Visualization, pp. 519–524 (2004)
Chen, T., Hsieh, L.: Uncovering the latent underlying domains of a research field: Knowledge visualization revealed. In: Information Visualization, 2006, pp. 252–256 (2006)
Fujishiro, I., Maeda, Y., Sato, H., Takeshima, Y.: Volumetric data exploration using interval volume. IEEE Transactions on Visualization and Computer Graphics 2(2), 144–155 (1996)
Guo, D., Chen, J., MacEachren, A., Liao, K.: A visualization system for space-time and multivariate patterns (vis-stamp). IEEE Transactions on Visualization and Computer Graphics 12(6), 1461–1474 (2006)
Kindlmann, G., Durkin, J.W.: Semi-automatic generation of transfer functions for direct volume rendering. In: IEEE Symposium on Volume Visualization, pp. 79–86 (1998)
Lum, E., Ma, K.-L., Clyne, J.: Texture hardware assisted rendering of time-varying volume data. In: Proceedings of IEEE Visualization, pp. 263–270 (2001)
Mansmann, F., Vinnik, S.: Interactive exploration of data traffic with hierarchical network maps. IEEE Transactions on Visualization and Computer Graphics 12(6), 1440–1449 (2006)
Qu, H., Chan, W.-Y., Xu, A., Chung, K.-L., Lau, K.-H., Guo, P.: Visual analysis of the air pollution problem in hong kong. IEEE Transactions on Visualization and Computer Graphics 13(6), 1408–1415 (2007)
Riley, K., Ebert, D., Hansen, C., Levit, J.: Visually Accurate Multi-Field Weather Visualization. In: Proceedings of IEEE Visualization, pp. 279–286 (2003)
Song, Y., Ye, J., Svakhine, N., Lasher-Trapp, S., Baldwin, M., Ebert, D.: An atmospheric visual analysis and exploration system. IEEE Transactions on Visualization and Computer Graphics 12(5), 1157–1164 (2006)
Sutton, P., Hansen, C.: Isosurface extraction in time-varying fields using a temporal branch-on-need tree (T-BON). In: Proceedings of IEEE Visualization, pp. 147–154 (1999)
Treinish, L.: Multi-resolution visualization techniques for nested weather models. In: Proceedings on IEEE Visualization, pp. 513–516 (2000)
Verma, V., Pang, A.: Comparative flow visualization. IEEE Transactions on Visualization and Computer Graphics 10(6), 609–624 (2004)
Weimer, H., Warren, J., Troutner, J., Wiggins, W., Shrout, J.: Efficient co-triangulation of large data sets. In: Proceedings on IEEE Visualization, pp. 119–126 (1998)
Wilkinson, L., Anand, A., Grossman, R.: High-dimensional visual analytics: Interactive exploration guided by pairwise views of point distributions. IEEE Transactions on Visualization and Computer Graphics 12(6), 1363–1372 (2006)
Wong, P., Foote, H., Mackey, P., Perrine, G., Chin, K.: Generating graphs for visual analytics through interactive sketching. IEEE Transactions on Visualization and Computer Graphics 12(6), 1399–1413 (2006)
Wood, J., Brodlie, K., Wright, H.: Visualization over the world wide web and its application to environmental data. In: Proceedings of IEEE Visualization, pp. 81–86 (1996)
Woodring, J., Shen, H.-W.: Multi-variate, time-varying, and comparative visualization with contextual cues. In: Proceedings of IEEE Visualization (2006)
Yuan, X., Nguyen, M., Chen, B., Porter, D.: Hdr volvis: high dynamic range volume visualization. IEEE transactions on Visualization and Computer Graphics 12(4), 433–445 (2006)
Zeiller, M.: A case study based approach to knowledge visualization. In: Ninth International Conference on Information Visualization, pp. 377–382 (2005)
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© 2009 Springer-Verlag Berlin Heidelberg
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Lu, A., Chen, W., Ribarsky, W., Ebert, D. (2009). Year-Long Time-Varying 3D Air Quality Data Visualization. In: Ras, Z.W., Ribarsky, W. (eds) Advances in Information and Intelligent Systems. Studies in Computational Intelligence, vol 251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04141-9_14
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DOI: https://doi.org/10.1007/978-3-642-04141-9_14
Publisher Name: Springer, Berlin, Heidelberg
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