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Let the Data Talk (ALA LLAMA MAES keynote 2012)
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Let the Data Talk (ALA LLAMA MAES keynote 2012)

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  • First maps were of the sky
    Cave paintings at Lascaux contain star maps
    Image from flickr user williamcromar
  • Maps of land came later.
    There seem to be several contenders for the first town map
    But here is a frequently cited example from Konya, Turkey in 6200 BCE
  • This graph by an unknown author attempts to show the movement of the planets over time.
    I can't vouch for its accuracy.
  • Rene Descartes – invents the Cartesian coordinate system
    This has significant impact on how we visualize quantitative information
  • William Playfair is credited with inventing statistical graphics.
    He invented the Bar Chart
    This is a later example that shows the rise in the price of wheat along with the rise in wages over time
  • Ben Schneiderman invented the treemap as a way to visualize usage of his Macintosh's hard drive.
    It's useful for displaying hierarchical data
  • Hans Rosling invents the Motion Bubble Chart – which is now part of Google's visualization API
    An interactive chart that displays several variables at once and animates changes over time.
    It's featured in a popular TED talk
  • Flickr user ketmonkey
  • Image from Casey Fleser
    An Osborne Executive portable computer, from 1982 with a Zilog Z80 4MHz CPU, and a 2007 Apple iPhone with a 412MHz ARM11 CPU. The Executive weighs 100 times as much, is nearly 500 times as large by volume, costs approximately 10 times as much (adjusting for inflation), and has 1/100th the clock frequency of the phone.
  • Flickr user ketmonkey
  • 1913 London Underground Map - http://homepage.ntlworld.com/clive.billson/tubemaps/1913.html
    Here is an example of a data visualization (or map) that is accurate but may not work well for its intended purpose.
    Things to notice
    It's a standard map project
    Subway lines appear where they would geographically if they were on the surface
    Roads, various municipal boundaries are visible.
    It works but it's not optimal
  • Harry Beck's 1933 Underground Map
    Beck took a step back
    Considered the problem that the subway map was attempting to solve
    What matters are relation of stops and transfer stations to each other
    Legibility of stop names – where to get on and off
    Subway is underground – don't need roads
    For simplicity and legibility lines are drawn at 90 and 45 degree angles
    – Similar to electrical circuit diagrams
    http://sites.google.com/site/tombowersites/harry-beck
  • 2010 Boston T Map
    This basic design is so successful that it is still used for subway maps around the world
  • Scatterplot – takes advantage of 2D spatial position
  • Line chart also takes advantage of 2D spatial position. Line chart is really a scatterplot with lines draw between points in some sequence.
  • Bar chart takes advantage of line length and 2D spatial position
  • Beyond asking good questions. Knowing the attributes that make for effective display of quantitative data, what are some guidelines etc. for visualizing data. There’s no magic bullet for creating effective data visualizations. It takes practice and experimentation. But there are some guiding principles that we help get you moving in the right direction.
  • Excel, Google Docs, Google Visualization API,
  • Somewhat like google gadgets but more powerful.
    Google Visualization API
    Collection of JavaScript visualizations
    You can customize and embed in web pages
    Requires some programming know-how
  • Relatively simple Javascript embedded in a web page generates the chart.
    Can modify this directly and create a chart, but the data will be static.
  • Relatively simple Javascript embedded in a web page generates the chart.
    Can modify this directly and create a chart, but the data will be static.
  • Transcript

    • 1. LET THE DATA TALK ALA Anaheim 2012 LLAMA – MAES Cory Lown Digital Technologies Development Librarian North Carolina State University Libraries
    • 2. 16,500 BCE
    • 3. 6,200 BCE
    • 4. 950
    • 5. 1637
    • 6. 1786
    • 7. 1991
    • 8. 2005
    • 9. Computers are useless. They can only give you answers. — Pablo Picasso
    • 10. Untitled Image Layout • Image of something built
    • 11. Untitled Image Layout • Image of a tool
    • 12. Psychophysics The branch of psychology that studies the relationship between physical stimuli and mental response
    • 13. Stimulus  Stimulation  Perception
    • 14. 9128732198432789543287 6784905043267812837698 7843928364382398731092 3478957438298374209123 0980934591283754845645 8934678238328009748349
    • 15. 9128732198432789543287 6784905043267812837698 7843928364382398731092 3478957438298374209123 0980934591283754845645 8934678238328009748349
    • 16. Preattentive attributes • Form – Orientation – Line length – Line width – Size – Shape – Curvature – Marks – Enclosure • Color – Hue – Intensity • Spatial Position – 2D
    • 17. Preattentive attributes • Form – Orientation – Line length – Line width – Size – Shape – Curvature – Marks – Enclosure • Color – Hue – Intensity • Spatial Position – 2D
    • 18. Preattentive attributes • Form – Orientation – Line length – Line width – Size – Shape – Curvature – Marks – Enclosure • Color – Hue – Intensity • Spatial Position – 2D
    • 19. THINGS TO THINK ABOUT Advice from Tufte & Few
    • 20. “Above all else show the data” – Edward Tufte
    • 21. Tables & Graphs
    • 22. Use Tables When you will need to look up individual values
    • 23. Use Tables When you will need to compare individual values
    • 24. Use Tables When precise values are required
    • 25. Use Graphs When the message is contained in the shape of values
    • 26. Use Graphs When there is a large amount of data
    • 27. Types of Graphs Different quantitative relationships require different forms of graphs. There are heuristics you can follow.
    • 28. Lines Perfect for expressing change over time.
    • 29. Points When you want to show whether two things are correlated use points.
    • 30. Bars These are great for showing the rank of things.
    • 31. Bars Also good for expressing part to whole relationships -- percentages.
    • 32. 2D area Use sparingly. This includes pie charts.
    • 33. Highlight the data
    • 34. Highlight the data by reducing non-data ink. Be stingy with ink.
    • 35. Highlight the data by reducing non-data ink. If I removed this would the graph lose meaning?
    • 36. Highlight the data by reducing non-data ink. De-emphasize supporting components such as grid lines
    • 37. Highlight the data by enhancing data ink. Emphasize the most important data by using width, orientation, size, enclosure, hue, color intensity.
    • 38. Highlight the data by enhancing data ink. But don't overemphasize.
    • 39. Organize Group, prioritize, and sequence data to help viewers understand.
    • 40. Too much data? Try small multiples.
    • 41. TOOLS
    • 42. Untitled Image Layout
    • 43. http://selection.datavisualization.ch/
    • 44. READERS’ ADVISORY
    • 45. Edward Tufte The Visual Display of Quantitative Information
    • 46. Stephen Few Show Me the Numbers: Designing Tables and Graphs to Enlighten
    • 47. Christopher Healey Perception in Visualization http://www.csc.ncsu.edu/faculty/he aley/PP/
    • 48. THANK YOU Cory Lown NCSU Libraries cwlown@ncsu.edu

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