The course: An Introduction to Information Visualization Techniques for Exploring Large Database

Transcription

1 The course: An Introduction to Information Visualization Techniques for Exploring Large Database Jing Yang Fall Multi-dimensional Data Visualization 2 1

2 Parallel Coordinates 3 Stick Figures 5-dim. image data from the great lake region used without permission of G. Grinstein, University of Massachusetts at Lowell 4 2

3 Query-Independent Techniques Recursive pattern arrangements The figure is taken from Dr. D. Keim s tutorial notes with his permission. 5 Eureka (Table Lens) 6 3

4 Hierarchy and Tree Visualization 7 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): ,

5 Space-Optimized Tree [Q. Nguyen and M. Huang Infovis 02] Key idea: Partition display space into a collection of geometrical areas for all nodes Use node-link diagrams to show relational structure Example: Tree with 150 nodes Example: Tree with approximately nodes 3D Tree Tavanti and Lind, InfoVis 01. Used without their permission. 10 5

6 Cone Tree Robertson, Mackinlay, Card CHI Alternative Views of Cone Tree Robertson, Mackinlay, Card CHI

7 Hyperbolic Brower R. Spence. Information Visualization. Used without permission. 13 Botanical Tree [E. Kleiberg et. al. InfoVis 2001] Botanical tree: Final model with the improvements 14 7

8 Marketmap 15 Radial Space Filing Techniques InterRing [Yang02] 16 8

9 Graph Visualization Node-line diagram Call Matrix 17 H3 viewer 18 9

10 Time-Series Data Visualization 19 Wireframe Solution Moving from one time slice to another with a wireframe and variable translucency

11 Spiral Graphs History of Italian post office A. Gabaglio, Space and Time Life circle of Japanese Beetles L. Newman, Man and Insects,

12 Space and Time Afghanistan in 2002 Events in three weeks Shootings Bombings Fires Mines Kidnaps Thefts assaults 23 Shape 24 12

13 Usability Inspection in UI Figure 6.1: Survey with regard to frequencies of methods used and usefulness rating of them [Nie95] 25 Visual Perception Ware

14 Interaction Techniques 27 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 28 permission. 14

15 Large Dataset Visualization Left to right: original, intensity, histogram approaches 29 Large Dataset Visualization Hierarchical Parallel Coordinates for Exploration of Large Datasets Fua et. al. Vis99 The following slides are from Fua s presentation 30 15

16 Challenge - Dimension Relationship Visualization (con.) Recall data item relationship visualization: MDS: SPIRE Galaxies [Wise:95] Hint: Using MDS to layout dimensions SPIRE Galaxies: Map data items to a 2D display using MDS [Wise: 95] 31 Value and Relation Display Features: Explicitly conveys data values without dimension reduction Explicitly conveys dimension relationships Provides a rich set of interaction tools SkyServer dataset: dimensions, 50,000 data items 16

17 Clustering CURE [GRS98] 33 Multi-Dimensional Histograms Paper: Approximating Multi-Dimensional Aggregate Range Queries over Real Attributes (D. Gunopulos, G. Kollios, V. Tsotras, and C. Domeniconi. 2000) 34 17

18 THREAD ARCS: An Thread Visualization [Kerr Infovis 2003] Prototype: 35 Chat Circles [Viegas and Donath CHI 99] 36 18

19 Garden Combine many portraits to make a garden Message board with 1200 postings over 2 months Each flower is a different user Height indicates length of time at the board 37 SeeSoft System View 38 19

20 POLKA [Stasko & Kraemer JPDC 93] Improved animation design model Object-oriented paradigm Multiple animation windows Much richer visualization/anim ation capabilities 39 Enhanced Presentation of a Document Document Lens 40 20

21 Topic Islands [Miller Vis 98] 41 Natto [Shiozawa and Matsushita HCI International '97] 42 21

22 Open Text Web Index [Tim Bray 1996] 43 (a) Males (b) Females Gender Differences: Males tend to navigate in specific, direct patterns, whereas women s navigation patterns include more browsing, utilizing more of the site

23 GeneSpring The largest variety of visualizations for microarray data analysis 45 Summary In the course, we will discuss: 1. Basic multivariate, tree, and graph visualization techniques 2. Basic interaction techniques 3. Theory and design principles 4. Recent approaches to exploring large datasets 5. Information visualization applications 6. Contents by requests from students 46 23