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Info Vis: Multi-Dimensional Data

Info Vis: Multi-Dimensional Data. Chris North cs3724: HCI. Presentations. jerome holman john gibson Vote: UI Hall of Fame/Shame?. Quiz. Why visualization? Class motto:. Visualization Design Principles. Increase Data Density. Calculate data/pixel.

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Info Vis: Multi-Dimensional Data

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  1. Info Vis:Multi-Dimensional Data Chris North cs3724: HCI

  2. Presentations • jerome holman • john gibson • Vote: UI Hall of Fame/Shame?

  3. Quiz • Why visualization? • Class motto:

  4. VisualizationDesign Principles

  5. Increase Data Density • Calculate data/pixel “A pixel is a terrible thing to waste.”

  6. Eliminate “Chart Junk” • How much “ink” is used for non-data? • Reclaim empty space (% screen empty) • Attempt simplicity(e.g. am I using 3djust for coolness?)

  7. Information Visualization Mantra • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand • Overview first, zoom and filter, then details on demand

  8. InfoVis Design Principles • Increase data density • Eliminate “chart junk” • Mantra: Overview first, zoom&filter, details on demand • Insight factor • Does the design reveal the data? • Does the design help me explore, learn, understand? • Show me the data!

  9. Visualizing Multi-dimensional data

  10. Multi-dimensional Data Table Attributes (aka: dimensions, fields, variables, columns, …) • Data Values • Data Types: • Quantitative • Ordinal • Categorical/Nominal Items (aka: data points, records,tuples, rows, …)

  11. Basic Visualization Model Data Visual Mapping Visualization Interaction

  12. Visual Mapping • Map: data items  visual marks • Visual marks: • Points • Lines • Areas • Volumes

  13. Visual Mapping • Map: data items  visual marks • Map: data item attributes  visual mark attributes • Visual mark attributes: • Position, x, y • Size, length, area, volume • Orientation, angle, slope • Color, gray scale, texture • Shape

  14. Example • Hard drives for sale: • price ($), capacity (MB), quality rating (1-5) p c

  15. Example: Spotfire • Film database • Year  X • Length  Y • Popularity  size • Subject  color • Award?  shape

  16. Ranking Visual Attributes • Position • Length • Angle, Slope • Size • Color Increased accuracy for quantitative data -W.S. Cleveland Color better for categorical data -J. Mackinlay

  17. Basic Charts…

  18. Factors in Visualization Design • User tasks • Data • Data scale: • # recs • # attrs • # possible data values

  19. Data Scale • # of attributes (dimensionality) • # of items • # of possible values (e.g. bits/value)

  20. Spotfire • Multiple views: brushing and linking • Dynamic Queries • Details window

  21. TableLens (Eureka by Inxight) • Visual encoding of cell values, sorting • Details expand within context

  22. Parallel Coordinates • Bag cartesian orthogonal layout • Parallel axes • Data point = connected line segment • (0, 1, -1, 2) = x y z w 0 0 0 0

  23. Parallel Coordinates (XmdvTool)

  24. Parallel Coordinates

  25. Info. Vis. Topics • Information types: • Multi-dimensional: databases,… • 1D, 2D, 3D • Trees, Graphs • Text, document collections • Interaction strategies: • Overview+Detail • Focus+Context • Zooming • How (not) to lie with visualization

  26. Homework #2: Info. Vis. Tools • Get some data: • Tabular, >=5 attributes (columns), >=500 items (rows) • Use 2 visualization tools + Excel: • Spotfire, TableLens, Parallel Coordinates • Mcbryde 104c • 2 page report: • Discoveries in data • Comparison of tools • Due: • Feb 19: A-K • Feb 21: L-Z

  27. Project 2: Java • 3 students per team • Ambitious project • 0: form team (feb 14) • 1: design (feb 28) • 2: initial implementation (mid march) • 3: final implementation (end march)

  28. Next Presentations: proj1 design, UI critique • Thurs: john randal, tom shultz • Next Tues: mohamed hassoun, aaron dalton • Next Thurs: nadine edwards, steve terhar

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