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Data visualization

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Data visualization
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Data visualization

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This slide deck gives a general overview of Data Visualization, with inspiring examples, the strength and weaknesses of the human visual system, a few technical frameworks that may be used for creating your own visualizations and some design concepts from the data visualization field.

This slide deck gives a general overview of Data Visualization, with inspiring examples, the strength and weaknesses of the human visual system, a few technical frameworks that may be used for creating your own visualizations and some design concepts from the data visualization field.

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Data visualization

  1. Data Visualization
  2. Outline • What? • Why? • How?
  3. Outline • What? • Why? • How?
  4. Data Visualization “...to convey information through visual representations.” “...produces (interactive) visual representations of abstract data to reinforce human cognition; thus enabling the viewer to gain knowledge about the internal structure of the data and causal relationships in it.”
  5. Outline • What? • Why? • How?
  6. VISUALIZATION GOALS
  7. Visualization Goals • Answer questions (or discover them) • Make decisions • See data in context • Support graphical calculation • Find patterns • Present argument or tell a story • Inspire
  8. Three Functions of Visualization • Record: store information • Analyze: support reasoning about information • Communicate: convey information to others
  9. PERCEPTION & COGNITION
  10. Anscombe Quartet
  11. Anscombe Quartet
  12. How many 3’s? 24872184012387409216590147609856093247209 12562906509852659048275829856809609863095 84390564095878950374509284750989475092984
  13. How many 3’s? 24872184012387409216590147609856093247209 12562906509852659048275829856809609863095 84390564095878950374509284750989475092984
  14. Preattentive Processing • Requires attention despite the name • Very fast: < 200-250 ms • What matters most is the contrast between features
  15. Color
  16. Shape
  17. Conjunction
  18. Change Blindness
  19. Simultaneous Contrast
  20. Outline • What? • Why? • How?
  21. FRAMEWORKS
  22. ProtoVis
  23. Processing Spde
  24. REDESIGN
  25. INSPIRATION
  26. Credits & Resources • HansPeter Phister for slides inspiration: http://www.cs171.org/ • Stephen Few for Dashboard & redesigns: http://www.perceptualedge.com • Christopher G. Healy for Change Blindness & Preattentive Variables: http://www.csc.ncsu.edu/faculty/healey/PP/ • Hans Rosling from Gapminder: http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html http://www.gapminder.org/ • Protovis: http://vis.stanford.edu/protovis/ • Polymaps: http://www.polymaps.org/ • Processing: http://processing.org/ • Processing.js: http://processingjs.org/ • Spde: http://technically.us/spde/About • Tableau Public: http://www.tableausoftware.com/public/ • Oakland Crime Spotting & Cab Spotting by Stamen Design: http://www.stamen.com/ • “Good Morning” & Haiti Earthquake Aid in Avatar Minutes by Jer Thorp: http://blog.blprnt.com/ • House of Cards video clip for Radiohead by Aaron Koblin: http://www.aaronkoblin.com/ • Wikipedia history flow by Martin Wattenberg & Fernanda Viegaz: http://www.bewitched.com/ http://fernandaviegas.com/ • Map of USA by Ben Fry: http://benfry.com/ • “Hoe de kredietcrisis de beurs besmette by Frédérik Ruys: http://www.vizualism.com/ • StemBesef by Jan Willem Tulp: http://www.janwillemtulp.com/stembesef

Editor's Notes

  • http://www.csc.ncsu.edu/faculty/healey/PP/index.html

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