# 3 Information Visualization

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1 3 Information Visualization 3.1 Motivation and Examples 3.2 Basics of Human Perception 3.3 Principles and Terminology 3.4 Standard Techniques for Visualization 3.5 Further Examples Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Space-Scale Diagrams (Furnas & Bederson 95) User has a fixed-sized viewing window Moving it through 3D space yields all possible sequences of pan & zoom Marti Hearst Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-111

2 Space-Scale Diagrams (Furnas & Bederson 95) A point is transformed to a ray Circular regions become cones Marti Hearst Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Space-Scale Diagrams (Furnas & Bederson 95) If you move the origin of the 2D plane, the properties of the original 2D picture do not change Therefore, the absolute angles between the rays should not be assigned any meaning Marti Hearst Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-113

3 Space-Scale Diagrams (Furnas & Bederson 95) We can think of this in terms of 1D too When zoomed out, you can see wider set of points Marti Hearst Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Space-Scale Diagrams (Furnas & Bederson 95) Pure pan (a) Pure zoom (b) Pan and zoom keeping q in same position in the viewing window (c) Marti Hearst Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-115

4 Semantic Zooming Geometric (standard) zooming: The view depends on the physical properties of what is being viewed Semantic Zooming: When zooming away, instead of seeing a scaled-down version of an object, see a different representation The representation shown depends on the meaning to be imparted. Marti Hearst Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Semantic Zoom in MedioVis Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-117

5 Arc Diagrams Visualization method for representing complex patterns of repetition in string data. Arc diagrams scale efficiently for strings that contain many instances of the same subsequence. idea of visualizing only a subset of all possible pairs of matching substrings. highlight just the subsequences essential to understanding the string!s structure Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Arc Diagrams - Basics Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-119

6 Arc Diagram Level of Detail Applied to Music DNA Web pages Byte code Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Arc Diagram applied to Music Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-121

7 Arc Diagram applied to Music für Elise More details Martin Wattenberg. Arc Diagrams: Visualizing Structure in Strings IBM Watson Research Center, Technical report Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Thread Arcs Thread Arcs combine the chronology of messages with the branching tree structure of a conversational thread Benefits Chronology Relationships Stability Compactness Attribute Highlighting Scale Interpretation/Sense Bernard Kerr, Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-123

8 Thread Arcs for s Visualization Linear layout of message nodes connected by relationship arcs. Each circular node represents a message in the thread. Chronology of the thread is encoded by the position The width of a Thread Arc is a linear function of the size of the thread Compact visualization if height is constrained Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Pseudo code for drawing a thread arc Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-125

9 Space of Possible Thread Arcs (5 Messages) Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Chronological Information in the Thread Arcs Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-127

10 Example Client using Thread Arcs Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Click stream Visualization Jeffrey Brainerd Barry Becker Case Study: E-Commerce Clickstream Visualization Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS!01) Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-129

11 Click stream Visualization Brainerd et al. Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Click stream Visualization Brainerd et al. Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-131

12 Click stream Visualization Brainerd et al. Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Click stream Visualization Brainerd et al. Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-133

13 Hyperbolic Browser In the hyperbolic plane, the circumference and area of a circle grow exponentially with its radius Allocate each node a wedge of the hyperbolic plane The node recursively places all its children within an arc of that wedge at an equal distance from itself far enough out so the children are separated by at least a minimum distance Parallel lines diverge in hyperbolic geometry each child!s wedge will span about the same angle as its parent!s but not children!s wedges will overlap Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Hyperbolic Tree Browser (Lamping et al. 95) Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-135

14 Inxight!s Hyperbolic Browser Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Hyperbolic Tree Views Nice demos on the Web This is a variation on it that might be more interesting» Decides dynamically which subsets of the data to show Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-137

15 TheBrain.com Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II D Desktop - switching virtual desktops in 3D Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-139

16 3D Desktop - switching virtual desktops in 3D Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II D Desktop - switching virtual desktops in 3D Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-141

17 Sun: Project Looking Glass functional 3D-Desktop Video ~ 6min Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Visualization on Mobile Devices Some common challenges Small screen Limited processing power Limited interaction Limited bandwidth to data source Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-143

18 Rectangular Fish Eye View saving bandwidth in transmission Rauschenbach, U.: "The Rectangular Fish Eye View as an Efficient Method for the Transmission and Display of Large Images", in: Proceedings of IEEE ICIP'99, Kobe, Japan, Oct , Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Rectangular Fish Eye View saving bandwidth in transmission Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-145

19 Providing context for map navigation Baudisch, P. and Rosenholtz, R. Halo: A Technique for Visualizing Off-Screen Locations. In Proceedings of CHI 2003, Fort Lauderdale, FL, April 2003,pp Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II Providing context for map navigation Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-147

20 Providing context for map navigation Ludwig-Maximilians-Universität München Prof. Hußmann Mensch-Maschine-Interaktion II 3-148

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