Space-Time Cube in Visual Analytics Gennady Andrienko Natalia Andrienko Natalia Andrienko http://geoanalytics.net/and in cooperation with P.Gatalsky, G.Fuchs, K.Vrotsou, I.Peca, C.Tominski, H.Schumann inspired by T.Hagerstrand, M-J Kraak , M-P Kwan and others inspired by T.Hagerstrand, M J Kraak , M P Kwan and others 1 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
A bit of STC history 1969/1970 1969/1970 1999/2000 M P K 1999/2000, M-P Kwan 2002/2003 MJ K 2002/2003, MJ Kraak+G,A*2 k G A*2 2 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Interactive space-time cube T Traditional functionality: diti l f ti lit - change of the viewpoint; - zooming in the spatial and temporal dimensions; zooming in the spatial and temporal dimensions; - moveable plane for additional temporal reference; - animation of the content of STC (aka waterfall); animation of the content of STC (aka waterfall); - selection of spatio-temporal objects to be displayed; - access to objects by pointing and dragging; - coordinated highlighting in multiple views; 3 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
STC everywhere 2012 2012 STC is visible to general public! 4 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Spatio-temporal data E Events t Time series Flows between places Trajectories of MPOs 5 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
STC for events 6 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
STC for events Clustering events, eliminating noise Cl t i t li i ti i Replacing point events by convex hulls Temporal zooming 7 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Spatial time series N Numeric attributes i tt ib t 8 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Spatial time series 9 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Spatial time series N Nominal attributes i l tt ib t 10 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Flows between places H Hourly dynamics of l d i f take-offs and flows between FR airports 11 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories 12 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories One day trajectory in space and time O d t j t i d ti ti time space 13 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories O One day trajectory in space and time d t j t i d ti stop t • morning part • evening part 14 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Space-time cube O One year trajectory… t j t 15 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Interactive space-time cube W We propose to add t dd - Clustering of trajectories by similarity of geometric properties (e.g. routes) f t i ti ( t ) … - dynamic time transformation with respect to temporal cycles with respect to the individual lifelines of the trajectories 16 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Clustering of trajectories 17 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Time transformation in space-time cube Transformations with respect to temporal cycles, which include T f ti ith t t t l l hi h i l d - bringing the times of the trajectories to the same year or season, - the same month, the same month - week, - day, day, - hour Transformations with respect to the individual lifelines of the trajectories, p j , which include - bringing the trajectories to a common start moment, - a common end moment, - common start and end moments VAST 2010, ICC 2011 18 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Transformations with respect to temporal cycles: days 19 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Transformations with respect to temporal cycles: weeks 20 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Transformations with respect to individual lifelines 21 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
STC for trajectory attributes? Si Single cluster l l t Transformations with respect to with respect to temporal cycles: days 22 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectory wall – focus on trajectory attributes Time ordering (joint work with C Tominski & H Schumann InfoVis 2012) Time ordering (joint work with C.Tominski & H.Schumann, InfoVis 2012) 23 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectory wall – focus on trajectory attributes Time ordering Time ordering 24 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectory wall: traffic jam patterns in 4,000+ trajectories, 7 days 25 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectory wall t tortuosity t it 26 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
STC showing frequent sequences of visited places I D I.Drecki & P.Forer, 2000 ki & P F 2000 D O D.Orellana et al, 2011 ll t l 2011 Andrienko*2, Bursch, Weiskopf, VAST 2012 27 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories + related events E Encounters t {of different kinds} 28 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Rotterdam data (S. van der Spek), cinema 29 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Rotterdam data (S. van der Spek), Dudok 30 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories + related events: a hint for semantic interpretation stops t 31 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories + related events: cross-filtering encounters t 32 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Trajectories + related events: cross-filtering d ifti drifting 33 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Open question: what’s about movement in 3D? 34 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
Conclusion VA benefits from representing different types of spatio-temporal data in STC VA b fit f ti diff t t f ti t l d t i STC Data selection - Attribute-based, spatial, and temporal filtering - Clustering and subsequent interactive filtering - Search for frequent sequences, subsequent interactive filtering Search for freq ent seq ences s bseq ent interacti e filtering - Cross-filtering of multiple ST datasets Data transformation Data transformation - Event extraction - Deriving flows from trajectories Deriving flows from trajectories - Computing time series of attributes Open questions: p q Specific interactivity p y - 3D geodata? - time transformations - usability / guidelines 35 Space-Time Cube in Visual Analytics MOVE STC worskhop, Enschede NL, June 2012 http://geoanalytics.net
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