Abstract
A major task of spatio-temporal data analysis is to discover relationships and patterns among spatially and temporally scattered events. A most common analytic method is to plot them on a 3D chart with latitude, longitude and time being the three dimensions. The first drawback of this technique is that it fails to scale well when there are thousands of concentrated events since they suffer from cluttering, occlusion and other limitations of 3D plots. Second, it is hard to track the time component if the events are clustered in a region. To overcome these, we present a novel 2D visualization technique called Storygraph that provides an integrated view of location and time. Based on Storygraph, we also present storylines which show the movement of the characters over time. Finally, we present two case studies to demonstrate the effectiveness of the Storygraph.
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References
Hägerstrand, T., et al.: Time-geography: focus on the corporeality of man, society, and environment. The Science and Praxis of Complexity, 193–216 (1985)
Aigner, W., Miksch, S., Mller, W., Schumann, H., Tominski, C.: Visualizing time-oriented dataa systematic view. Computers and Graphics 31, 401–409 (2007)
Aigner, W., Miksch, S., Muller, W., Schumann, H., Tominski, C.: Visual methods for analyzing time-oriented data. IEEE Transactions on Visualization and Computer Graphics 14, 47–60 (2008)
Fisher, D., Hoff, A., Robertson, G., Hurst, M.: Narratives: A visualization to track narrative events as they develop. In: Proceedings of IEEE Symposium on Visual Analytics Science and Technology, pp. 115–122 (2008)
Vrotsou, K., Johansson, J., Cooper, M.: Activitree: Interactive visual exploration of sequences in event-based data using graph similarity. IEEE Transactions on Visualization and Computer Graphics 15, 945–952 (2009)
Javed, W., McDonnel, B., Elmqvist, N.: Graphical perception of multiple time series. IEEE Transactions on Visualization and Computer Graphics 16, 927–934 (2010)
Gschwandtner, T., Aigner, W., Kaiser, K., Miksch, S., Seyfang, A.: Carecruiser: Exploring and visualizing plans, events, and effects interactively. In: Proceedings of IEEE Pacific Visualization Symposium (PacificVis), pp. 43–50 (2011)
Geng, Z., Peng, Z., Laramee, R., Walker, R., Roberts, J.: Angular histograms: Frequency-based visualizations for large, high dimensional data. IEEE Transactions on Visualization and Computer Graphics 17, 2572–2580 (2011)
Zhao, J., Chevalier, F., Pietriga, E., Balakrishnan, R.: Exploratory analysis of time-series with chronolenses. IEEE Transactions on Visualization and Computer Graphics 17, 2422–2431 (2011)
Krstajic, M., Bertini, E., Keim, D.: Cloudlines: Compact display of event episodes in multiple time-series. IEEE Transactions on Visualization and Computer Graphics 17, 2432–2439 (2011)
Asgary, A., Ghaffari, A., Levy, J.: Spatial and temporal analyses of structural fire incidents and their causes: A case of toronto, canada. Fire Safety Journal 45, 44–57 (2010)
Plug, C., Xia, J.C., Caulfield, C.: Spatial and temporal visualisation techniques for crash analysis. Accident Analysis and Prevention 43, 1937–1946 (2011)
Jern, M., Franzen, J.: “Geoanalytics” - exploring spatio-temporal and multivariate data. In: Proceedings of Tenth International Conference on Information Visualization, pp. 25–31 (2006)
Maciejewski, R., Rudolph, S., Hafen, R., Abusalah, A., Yakout, M., Ouzzani, M., Cleveland, W., Grannis, S., Ebert, D.: A visual analytics approach to understanding spatiotemporal hotspots. IEEE Transactions on Visualization and Computer Graphics 16, 205–220 (2010)
Gatalsky, P., Andrienko, N., Andrienko, G.: Interactive analysis of event data using space-time cube. In: Proceedings of the Eighth International Conference on Information Visualisation, pp. 145–152 (2004)
Tominski, C., Schulze-Wollgast, P., Schumann, H.: 3D information visualization for time dependent data on maps. In: Proceedings of the Ninth International Conference on Information Visualisation, pp. 175–181 (2005)
Adrienko, G., Adrienko, N., Mladenov, M., Mock, M., Politz, C.: Identifying place histories from activity traces with an eye to parameter impact. IEEE Transactions on Visualization and Computer Graphics 18, 675–688 (2012)
Landesberger, T.V., Bremm, S., Andrienko, N., Adrienko, G., Tekusova, M.: Visual analytics for categoric spatio-temporal data. In: Proceedings of IEEE Conference on Visual Analytics Science and Technology (VAST 2012), pp. 183–192 (2012)
Shaw, S.L., Yu, H.: A gis-based time-geographic approach of studying individual activities and interactions in a hybrid physical virtual space. Journal of Transport Geography 17, 141–149 (2009) ICT and the Shaping of Access, Mobility and Everyday Life
Guardian.co.uk: Afghanistan war logs 2003-2010 (2010)
UXO-LAO: Lao national unexploded ordnance programme annual report 2007 (2008)
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Shrestha, A., Zhu, Y., Miller, B., Zhao, Y. (2013). Storygraph: Telling Stories from Spatio-temporal Data. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41939-3_68
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DOI: https://doi.org/10.1007/978-3-642-41939-3_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41938-6
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