Geospatial Visual Analytics and Geovisualization in VisMaster (WP3.4)
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1 Geospatial Visual Analytics and Geovisualization in VisMaster (WP3.4) Gennady Andrienko Fraunhofer Institute IAIS Sankt Augustin Germany Heidrun Schumann University of Rostock Rostock Germany
2 What is geovisualization? the use of visual representations of geographic information for the exploration and analysis of the data and gaining understanding of the underlying phenomena GeoVis is not only about space but also about time! Purposes : scientific discovery education decision support characteristics of spatial data heterogeneous anisotropic continuous (measurements are not error) error in: > locations (projection, etc.) > distances (elevation; constraints; alternatives) > attributes (poor models; limited samples) > time complexities: > scale (features / processes scale dependent) > time-dependence of temporal data time is linear AND time is cyclical multiple embedded & overlapping cycles complexities > different granularities > different viewpoints (totally ordered, partially ordered) spatial and temporal questions we might wish to answer how is this landscape developing and what are the implications? where do we focus our housing improvement grants this year? can we characterize society spatially to improve services? what does our audit tell us about the geography of our services?
3 Example of Geospatial Visual Analytics: Spatio-temporal analysis of health data Details: Chr. Tominski, P. Schulze-Wollgast and H. Schumann: Visual Methods for Analyzing Human Health Data. In: N. Wickramasinghe, E. Geisler (editors), Encyclopedia of Healthcare Information Systems. Information Science Reference, Chr. Tominski: Event-Based Visualization for User- Centered Visual Analysis. PhD thesis, University of Rostock, 2006.
4 Example of Geospatial Visual Analytics: Transportation Scheduling OASIS EU-funded IP, Details: Gennady Andrienko, Natalia Andrienko, Ulrich Bartling Visual Analytics Approach to User-Controlled Evacuation Scheduling IEEE Visual Analytics Science and Technology (VAST 2007), pp & Information Visualization, v.7(1), 2008 Input data Interactive visual interfaces Scheduling algorithm Schedule Computational analysis module Secondary data User s evaluation feedback Queries
5 Example of geospatial visual analytics: analysis of trajectories Algorithms, other details: G.Andrienko, N.Andrienko, S.Wrobel Visual Analytics Tools for Analysis of Movement Data ACM SIGKDD Explorations, v.9(2), December 2007
6 Example of geospatial visual analytics: analysis of city traffic Algorithms, other details: Gennady Andrienko, Natalia Andrienko Spatio-temporal aggregation for visual analysis of movements IEEE Visual Analytics Science and Technology (VAST 2008) Proceedings, IEEE Computer Society Press, 2008, pp.51-58
7 WP3.4: Space and Time Visual analytics. Introduction Participants: Fraunhofer IAIS Institute for Intelligent Analysis and Information Systems, Sankt Augustin, Germany University Rostock, Germany London City University, UK University Zurich, Switzerland ITC International Institute for Geo-Information Science and Earth Observation, Enschede, The Netherlands University Pisa, Italy
8 Work Plan A questionnaire has been sent to researchers and practitioners with relevant expertise and experience: What are the major scientific achievements up to date related to visually enabled analysis of spatial, temporal, and spatio-temporal data? What are the most prominent application achievements (success stories) in science / public applications / business? What are the major research and application challenges? What research directions are of primary importance? Replies due: 24th of December, 2008 Additional respondents are welcome! Analyse and summarise the replies received Expert workshop "Spatial and Temporal Visual Analytics, Hamburg, March 2-3, 2009 (immediately before the workshop "Contribution of Geovisualization for the concept of the Digital City ) Contact: gennady.andrienko@iais.fraunhofer.de
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