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Lecture 05: Design

Lecture 05: Design

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Lecture 05: Design

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  1. Lecture 05:Design January 31, 2013 COMP 150-2Visualization

  2. Design • What is a good visualization (design)?

  3. 2008 Election Map Image courtesy of http://politicalmaps.org

  4. 2008 Election Map Image courtesy of http://politicalmaps.org

  5. 2008 Election Map Image courtesy of http://politicalmaps.org

  6. Data Is (Usually) Coherent

  7. White Noise

  8. Good Design Reveals Patterns • 100,000 computers colored by IP addresses in 1998.

  9. Snow’s Map of Cholera

  10. Edward Tufte • “The Visual Display of Quantitative Information” • Self-published book • Evangelist for good visual design • Most designs are static, but many principles apply to interactive (computer-based) visualization designs • Take these design guidelines with a grain of salt

  11. Graphical Excellence • Tufte’s Principles of Graphical Excellence • Graphical excellence is the well-designed presentation of interesting data – a matter of substance, of statistics, and of design.

  12. Graphical Excellence • Tufte’s Principles of Graphical Excellence • Graphical excellence is the well-designed presentation of interesting data – a matter of substance, of statistics, and of design. • Graphical excellence consists of complex ideas communicated with clarity, precision, and efficiency.

  13. Graphical Excellence • Tufte’s Principles of Graphical Excellence • Graphical excellence is the well-designed presentation of interesting data – a matter of substance, of statistics, and of design. • Graphical excellence consists of complex ideas communicated with clarity, precision, and efficiency. • Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink the smallest place.

  14. Graphical Excellence • Tufte’s Principles of Graphical Excellence • Graphical excellence is the well-designed presentation of interesting data – a matter of substance, of statistics, and of design. • Graphical excellence consists of complex ideas communicated with clarity, precision, and efficiency. • Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink the smallest place. • Graphical excellence is nearly always multivariate

  15. Graphical Excellence • Tufte’s Principles of Graphical Excellence • Graphical excellence is the well-designed presentation of interesting data – a matter of substance, of statistics, and of design. • Graphical excellence consists of complex ideas communicated with clarity, precision, and efficiency. • Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink the smallest place. • Graphical excellence is nearly always multivariate • And graphical excellence requires telling the truth about the data.

  16. Napoleon’s March to Moscow

  17. Minard’sMap ofNapoleon’s March to Moscow

  18. Graphical Integrity • “Above all else show the data”

  19. The Lie Factor • Tufte coined the term “the lie factor”, which is defined as: • Lie_factor = • “High” lie factor (LF) leads to: • Exaggeration of differences or similarities • Deception • Misinterpretation

  20. The Lie Factor • The Lie Factor (LF) can be • LF > 1 • LF < 1 • If LF is > 1, then size of graphic is greater than the size of data • This leads to exaggeration of the data (overstating the data) • If LF < 1, then the size of the data is greater than the graphic • This leads to hiding the of data (understating the data)

  21. What’s Wrong With This? • US Department of Transportation had set a series of fuel economy standards to be met by automobile manufacturers, beginning with 18 miles per gallon in 1978 and moving in steps up to 27.5 by 1985.

  22. What’s Wrong With This? This line represents 18 miles per gallon in 1976, is 0.6 inches long This line represents 27.5 miles per gallon in 1985, is 5.3 inches long

  23. What’s Wrong With This? • The increase in real data between 1978 to 1985 (from 18 MPG to 27.5 MPG) is: • The difference in length between 1978 to 1985 (from 0.6 inches to 5.3 inches) is: • Lie Factor is:

  24. Similarly • This design contains a lie factor of 9.4

  25. Similarly • This design contains a lie factor of 9.5

  26. Other Ways To Lie(with the legend)

  27. Other Ways To Lie(with the encoding)

  28. Other Ways To Lie(with the design variation)

  29. Other Ways To Lie(with the design variation) • Beware of the “3D” effect. It distorts the telling of the data. • There are five vertical scales here: • 1073-1978: • 1 inch = $8.00 • Jan-Mar: • 1 inch = $4.73 • Apr – Jun • 1 inch = $4.37 • Jul – Sep • 1 inch = $4.16 • Oct – Dec • 1 inch = $3.92 • And two horizontal scales: • 1973-1978: • 1 inch = 3.8 years • 1979 • 1 inch = 0.57 years

  30. Other Ways To Lie(with the design variation) • The 3D chart capability in Excel:

  31. Other Ways To Lie(with double-encoding, e.g. size) • Here, both width and height encode the same information. The effect is multiplicative. • 0.44 (width) * 0.44 (height) = 0.19

  32. Other Ways To Lie(with unintended encoding)

  33. Other Ways To Lie(with unintended encoding) • Are we encoding height, area, or volume?

  34. Other Ways To Lie(with alignment)

  35. Other Ways To Lie(with limited context)

  36. Other Ways To Lie(with limited context)

  37. Other Ways To Lie(with limited context)

  38. Other Ways To Lie(with limited context)

  39. Other Ways To Lie(with limited context)

  40. Questions?

  41. Questions?

  42. Design Principles for Graphical Integrity • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented. • Clear, detailed, and thorough labeling should be used to defeat graphical distortions and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data. • Show data variation, not design variation. • The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. • Graphics must not quote data out of context.

  43. Design Principles for Graphical Integrity • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented. • Clear, detailed, and thorough labeling should be used to defeat graphical distortions and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data. • Show data variation, not design variation. • The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. • Graphics must not quote data out of context.

  44. Design Principles for Graphical Integrity • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented. • Clear, detailed, and thorough labeling should be used to defeat graphical distortions and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data. • Show data variation, not design variation. • The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. • Graphics must not quote data out of context.

  45. Design Principles for Graphical Integrity • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented. • Clear, detailed, and thorough labeling should be used to defeat graphical distortions and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data. • Show data variation, not design variation. • The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. • Graphics must not quote data out of context.

  46. Design Principles for Graphical Integrity • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented. • Clear, detailed, and thorough labeling should be used to defeat graphical distortions and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data. • Show data variation, not design variation. • The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. • Graphics must not quote data out of context.

  47. Data-Ink • “Maximize the Data-Ink Ratio”

  48. The Concept of Data-Ink Ratio • Data-Ink Ratio =

  49. Data-Ink Ratio • The goal is to aim for high data-ink ratio • Ink used for he data should be relatively large compared to the ink in the entire graphic • Can be thought of as: “proportion of a graphics ink devoted to the non-redundant display of data-information.” • Or, “1.0 – proportion of a graphic that can be erased without loss of data-information.”