Landesberger, Tatiana von and Bremm, Sebastian and Andrienko, Natalia and Andrienko, Gennady and Tekusová, Maria (2012):
Visual Analytics Methods for Categoric Spatio-Temporal Data.
IEEE Press, New York, In: IEEE Conference on Visual Analytics Science and Technology 2012. Proceedings, DOI: 10.1109/VAST.2012.6400553, [Conference or Workshop Item]
Abstract
We focus on visual analysis of space- and time-referenced categorical data, which describe possible states of spatial (geographical) objects or locations and their changes over time. The analysis of these data is difficult as there are only limited possibilities to analyze the three aspects (location, time and category) simultaneously. We present a new approach which interactively combines (a) visualization of categorical changes over time; (b) various spatial data displays; (c) computational techniques for task-oriented selection of time steps. They provide an expressive visualization with regard to either the overall evolution over time or unusual changes. We apply our approach on two use cases demonstrating its usefulness for a wide variety of tasks. We analyze data from movement tracking and meteorologic areas. Using our approach, expected events could be detected and new insights were gained.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2012 |
| Creators: | Landesberger, Tatiana von and Bremm, Sebastian and Andrienko, Natalia and Andrienko, Gennady and Tekusová, Maria |
| Title: | Visual Analytics Methods for Categoric Spatio-Temporal Data |
| Language: | English |
| Abstract: | We focus on visual analysis of space- and time-referenced categorical data, which describe possible states of spatial (geographical) objects or locations and their changes over time. The analysis of these data is difficult as there are only limited possibilities to analyze the three aspects (location, time and category) simultaneously. We present a new approach which interactively combines (a) visualization of categorical changes over time; (b) various spatial data displays; (c) computational techniques for task-oriented selection of time steps. They provide an expressive visualization with regard to either the overall evolution over time or unusual changes. We apply our approach on two use cases demonstrating its usefulness for a wide variety of tasks. We analyze data from movement tracking and meteorologic areas. Using our approach, expected events could be detected and new insights were gained. |
| Publisher: | IEEE Press, New York |
| Uncontrolled Keywords: | Forschungsgruppe Visual Search and Analysis (VISA), Visual analytics, Information visualization, Time series analysis, Spatio-temporal data |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Event Title: | IEEE Conference on Visual Analytics Science and Technology 2012. Proceedings |
| Date Deposited: | 12 Nov 2018 11:16 |
| DOI: | 10.1109/VAST.2012.6400553 |
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