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The course:An Introduction to Information Visualization Techniques for Exploring Large Database
Jing YangFall 2006
www.cs.uncc.edu/~jyang13
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Multi-dimensional Data Visualization
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Parallel Coordinates
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Stick Figures
http://ivpr.cs.uml.edu/gallery/used without permission of G. Grinstein, University of Massachusetts at Lowell
5-dim. imagedata from thegreat lake region
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Query-Independent Techniques
Recursive pattern arrangements
The figure is taken from Dr. D. Keim’s tutorial notes with his permission.
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Eureka (Table Lens)
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Hierarchy and Tree Visualization
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A Classical Hierarchical View
Position children “below” their common ancestors
Layout can be top-down, left-to-right and grid like positioning
Fast: linear time
E. Reingold and J. Tilford. Tidier drawing of trees. IEEE Trans. Softw. Eng., SE-7(2):223-- 228, 1981
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Space-Optimized Tree [Q. Nguyen and M. Huang Infovis 02]
Key idea:Partition display space into a collection of geometrical areas for all nodesUse node-link diagrams to show relational structure
Example: Tree with approximately 55000 nodes
Example: Tree with 150 nodes
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3D Tree
Tavanti and Lind, InfoVis 01. Used without their permission.
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Cone Tree
Robertson, Mackinlay, Card CHI ‘91
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Alternative Views of Cone Tree
Robertson, Mackinlay, Card CHI ‘91
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Hyperbolic Brower
R. Spence. Information Visualization. Used without permission.
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Botanical Tree [E. Kleiberg et. al. InfoVis 2001]
Botanical tree:
Final model with the improvements
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Marketmap
http://www.smartmoney.com/marketmap/
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Radial Space Filing Techniques
InterRing [Yang02]
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Graph Visualization
Node-line diagram Call Matrix
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H3 viewer
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Time-Series Data Visualization
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Wireframe Solution
Moving from one time slice to another with a wireframe and variable translucency.
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Spiral Graphs
History of Italian post office A. Gabaglio, 1888
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Space and Time
Life circle of Japanese Beetles L. Newman, Man and Insects, 1965
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Space and Time
Afghanistan in 2002Events in three weeks
ShootingsBombingsFiresMinesKidnapsTheftsassaults
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Shape
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Usability Inspection in UI
Figure 6.1: Survey with regard to frequencies of methods usedand usefulness rating of them [Nie95]
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Visual Perception
Ware 2004
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Interaction Techniques
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Multi-Resolution Visualization
Restricted cognitive resources of human viewers
Example: A graph that contains 87,931 vertices and 87,930 edges [GKN04]. This figure is used without authors’permission.
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Large Dataset Visualization
Left to right: original, intensity, histogram approaches
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Large Dataset Visualization
Hierarchical Parallel Coordinates for Exploration of Large Datasets Fua et. al. Vis99The following slides are from Fua’s presentation
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Challenge - Dimension Relationship Visualization (con.)
SPIRE Galaxies: Map data items to a 2D display using MDS [Wise: 95]
Recall data item relationship visualization:MDS: SPIRE Galaxies [Wise:95]
Hint: Using MDS to layout dimensions
32SkyServer dataset: 361 dimensions, 50,000 data items
Value and Relation Display
Features: Explicitly conveys data values without dimension reductionExplicitly conveys dimension relationshipsProvides a rich set of interaction tools
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Clustering
CURE [GRS98]
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Multi-Dimensional Histograms
Paper: Approximating Multi-Dimensional Aggregate Range Queries over Real Attributes(D. Gunopulos, G. Kollios, V. Tsotras, and C. Domeniconi. 2000)
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THREAD ARCS: An Email Thread Visualization [Kerr Infovis 2003]
Prototype:
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Chat Circles [Viegas and DonathCHI’99]
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Garden
Combine many portraits to make a gardenMessage board with 1200 postings over 2 monthsEach flower is a different userHeight indicates length of time at the board
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SeeSoft System View
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POLKA [Stasko & Kraemer JPDC ’93]
Improved animation design modelObject-oriented paradigmMultiple animation windowsMuch richer visualization/animation capabilities
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Enhanced Presentation of a Document
Document Lens
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Topic Islands [Miller Vis 98]
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Natto [Shiozawa and Matsushita HCI International '97]
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Open Text Web Index [Tim Bray 1996]
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(a) Males (b) FemalesGender Differences: Males tend to navigate in specific, direct patterns, whereas women’s navigation patterns include more browsing, utilizing more of the site.
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GeneSpring
The largest variety of visualizations for microarray data analysis
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Summary
In the course, we will discuss:1. Basic multivariate, tree, and graph visualization techniques2. Basic interaction techniques3. Theory and design principles 4. Recent approaches to exploring large datasets5. Information visualization applications6. Contents by requests from students
