Outline. Fundamentals. Rendering (of 3D data) Data mappings. Evaluation Interaction

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1 Outline Fundamentals What is vis? Some history Design principles The visualization process Data sources and data structures Basic visual mapping approaches Rendering (of 3D data) Scalar fields (isosurfaces + volume rendering) Vector and tensor field visualization Data mappings Perception + Color High-dimensional data Graphs/Trees Time-varying data Evaluation Interaction 47

2 Techniques for finding visual representations for abstract data are not new! 48

3 Map of Catal Hyük 6200 BC Excavation Reconstruction 49

4 Map on clay of Ga-Sur 2500 BC Map on clay Reconstruction 50

5 Sung Dynasty, China (1137 BC) 51

6 Ptolemaic map of the world by Johan Scotus (1505 AD) 52

7 Time series: inclination of planets (10th century) 53

8 Map of tracks of Yü the Great (11th century) 54

9 Vector visualization (1686) Streamlines, arrow plots by Halley Height field (1879) Census data by Perozzo 55

10 Napoleon s campaign against Russia (1812/13) Cartography (1861) 56

11 1987 NSF Advisory Panel on Graphics and Image Processing Computer experiments allow access to new worlds Real experiments are too expensive, too dangerous, etc. Arbitrary large and small time scales and spatial dimensions Direct implications The data flood from supercomputer simulations can only be dealt with visually This task needs a visualization specialist and an interdisciplinary team New developments in hardware, software, nets, standards are necessary Advantages in the long term will be Faster insight Faster product development cycles Stronger position in global competition 57

12 Related Fields Signal/Image Processing Rendering/ Computer Graphics Vision Applied Mathematics Hardware Visualization User Interfaces Computational Geometry Psychology Cognition 58

13 Related Fields Taxonomy Volumes Surfaces Geometric model Voxelization discretization Surface extraction polygonalization Computer vision / pattern recognition Data visualization Sampling Scanning Computation / simulation CT, MRI, Scanners, Ultrasound Seismic sensors, cameras Computer graphics Image processing Image (signal) Supercomputers Numerical Simulations Display Video recording 59

14 Visualization Flavors Spatial Data Vis (aka: Scientific visualization) User Interfaces Data representation/processing Algorithms Visual representations Mainly: Continuous models Non-Spatial Data Vis (aka: Information visualization) Abstract data WWW documents File structures Arbitrary relationships 60

15 Further Reading Primary book on perception and visual design: C. Ware: Information Visualization: Perception for Design, Elsevier/Morgan Kaufmann, (1 st ed. 2000, 2 nd ed. 2004) First edition available online: isbn= Primary book(s) on Spatial Data / Volume Graphics C.D. Hansen, C.R. Johnson (eds.): The Visualization Handbook, Elsevier, 2005 K. Engel, M. Hadwiger, J.M. Kniss, C. Rezk-Salama, D. Weiskopf, Real-time volume graphics, AK Peters, 2006 Primary book(s) on Non-Spatial Data Ch. Chen, Information Visualization: Beyond the Horizon, Springer Verlag, 2004 Card, Mackinlay, and Shneiderman, (eds.), Readings in Information Visualization: Using Vision To Think; Morgan Kaufmann

16 Further Reading References: G.M. Nielson, H.Hagen, H. Müller: Scientific Visualization, IEEE Computer Society Press, Los Alamitos, 1997 W.J. Schroeder, K.W. Martin, B. Lorenson: The Visualization Toolkit: An Object- Oriented Approach to 3D Graphics, Kitware, Clifton Park The Visualization Toolkit User's Guide, Version 4.2, Kitware, 2003 E.R. Tufte, The Visual Display of Quantitative Information, Graphics Press 1983 E.R. Tufte, Envisioning Information, Graphics Press 1990 E.R. Tufte, Visual Explanations, Edward R. Tufte, Graphics Press

17 (Spatial) Visualization Tools Great / free: VTK (The Visualization Toolkit) ( Commercial tools: Amira AVS/Express IDL IRIS Explorer OpenDX (now open software): 63

18 (Non-Spatial) Vis. Tools Tamara s resources page! Free: Prefuse (java) Xgobi! Commercial tools: Tableau 64