1 / 37

Lecture 16 : Visualizations Summary

Lecture 16 : Visualizations Summary. April 2, 2011 COMP 150-7 Visualization. Data Types. Dimensionality 1D , 2D 3D Temporal Multi-dimensional ( nD ) Relationships Tree (hierarchy) Network Others Workspaces Text. Data Types. Dimensionality 1D , 2D – boring

steve
Download Presentation

Lecture 16 : Visualizations Summary

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Lecture 16:Visualizations Summary April 2, 2011 COMP 150-7Visualization

  2. Data Types • Dimensionality • 1D, 2D • 3D • Temporal • Multi-dimensional (nD) • Relationships • Tree (hierarchy) • Network • Others • Workspaces • Text

  3. Data Types • Dimensionality • 1D, 2D – boring • 3D – take the graphics course • Temporal • Multi-dimensional (nD) • Relationships • Tree (hierarchy) • Space Filling (e.g., Tree maps) • Node-Link (e.g., org charts) • Network • Others • Workspaces – huh? • Text – important, but not covered. Why?

  4. Visualization Examples • http://mbostock.github.com/protovis/ex/ • https://github.com/mbostock/d3/wiki/Gallery • http://www.tableausoftware.com/public/gallery • http://www-958.ibm.com/software/analytics/manyeyes/ • http://www.visual-literacy.org/periodic_table/periodic_table.html • TreeVis.net

  5. Equivalence in Visualizations? • TreeVis.net examples • Sunburst -> Icicle Plot -> Circle Hierarchy • Circle Hierarchy -> (top-down) Tree • Circle Hierarchy -> Nested Bubbles -> Treemap • Sunburst -> Reingold–TilfordTree • Others? • LineGraph -> Barchart -> Stacked Barchart -> ThemeRiver • (Conceptually Wrong, but cool-looking: http://bl.ocks.org/mbostock/1256572) • (Note the Horizon Graph)

  6. Temporal Data

  7. Challenges • Our short-term memory is terrible • Recall of specific event or instance from an animation is very difficult, especially when the visualization is abstract • Remember Hans Rosling’sGapminder • The questions are: • How to layout time? • Usually x-axis • Cultural differences? • How to find a pattern in time? • Visually? • Computation?

  8. X-Y Charts

  9. Side-Ways Bar

  10. ThemeRiver

  11. Radial Layout

  12. Multi-Dimensional Data

  13. Challenges • Our brain cannot handle high dimensional information • We see the world in 2.5D, our brain reconstructs 3D • Dimensionality higher than that is too abstract to “visualize” • The questions are: • How to see more than 2 dimensions? • Slice-and-Dice • Stacking • How to find correlations in Data? • Visually? • Computation?

  14. Small Multiples (Slice-and-Dice)

  15. Table Lens (Slice-and-Dice)

  16. Parallel Coordinates (Slice-and-Dice)

  17. Star-Graphs (Slice-and-Dice)

  18. nD to 2D Projection

  19. Hierarchical Data

  20. Challenges • Hierarchies occur everywhere, and can be used to represent lots of different things • A classic computer science issue • Problem is that hierarchies can be both “deep” and “wide” • The questions are: • How to utilize space effectively? • Space-filling • Node-link • How to find a pattern in the sub-branches? • Visually? • Computation?

  21. Types of Hierarchy Visualizations • Space Filling • Node-Link

  22. SequoiaView

  23. VoronoiTreemaps

  24. InterRing

  25. How to Draw This Tree? • How wide does this graph have to be?

  26. Icicle Plot

  27. 2D Hyperbolic Browser http://flare.prefuse.org/demo

  28. Other Space-Filling + Node-Link Graphs • Hilbert Curves

  29. H-Tree for Family-Tree

  30. Network Data

  31. Challenges • Thinking about many-to-many relationships is always challenging • Students vs. classes • Particularly tricky because of: • Directed vs. undirected edges • Cycles within the graph • The questions are: • Hairball problem • Too many edges, too many nodes – layout is very challenging • Interaction is a must • How to find a pattern in a network? • Visually? • Computation?

  32. What Makes a Graph? • Vertices (nodes) • Edges (links) • Adjacency list: • 1: 2 • 2: 1, 3 • 3: 2

  33. Circular Layout + Edge Bundling

  34. Matrix Representation Henry InfoVis 06

  35. NodeTrix Hybrid of matrix and node-link Best of both worlds? Worst of both methods? Henry InfoVis 07

  36. Temporal Data

More Related