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Introduction - Department of Computer Science Tufts University

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					  Lecture 01:
   Design

January 25, 2011

  COMP 150-7
  Visualization
                    Design




• What is a good visualization (design)?
2008 Election Map




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




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




                    Image courtesy of http://politicalmaps.org
Data Is (Usually) Coherent
White Noise
        Good Design Reveals Patterns




100,000 computers colored by IP addresses in 1998.
Snow’s Map of Cholera
              Graphical Excellence

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

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

• Tufte’s Principles of Graphical Excellence
  1. Graphical excellence is the well-designed
     presentation of interesting data – a matter of
     substance, of statistics, and of design.
  2. Graphical excellence consists of complex ideas
     communicated with clarity, precision, and efficiency.
  3. 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

• Tufte’s Principles of Graphical Excellence
  1. Graphical excellence is the well-designed
     presentation of interesting data – a matter of
     substance, of statistics, and of design.
  2. Graphical excellence consists of complex ideas
     communicated with clarity, precision, and efficiency.
  3. 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.
  4. Graphical excellence is nearly always multivariate
              Graphical Excellence

• Tufte’s Principles of Graphical Excellence
  1. Graphical excellence is the well-designed
     presentation of interesting data – a matter of
     substance, of statistics, and of design.
  2. Graphical excellence consists of complex ideas
     communicated with clarity, precision, and efficiency.
  3. 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.
  4. Graphical excellence is nearly always multivariate
  5. And graphical excellence requires telling the truth
     about the data.
Napoleon’s March to Moscow
      Minard’s Map of
Napoleon’s March to Moscow
             Graphical Integrity




• “Above all else show the data”
                   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
                      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)
         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.
           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
What’s Wrong With This?
                   Similarly




• This design contains a
  lie factor of 9.4
                Similarly



• This design
  contains a
  lie factor
  of 9.5
Other Ways To Lie
(with the legend)
 Other Ways To Lie
(with the encoding)
    Other Ways To Lie
(with the design variation)
                        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
               Other Ways To Lie
           (with the design variation)
• The 3D chart capability in Excel:
               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
     Other Ways To Lie
(with unintended encoding)
              Other Ways To Lie
         (with unintended encoding)


• Are we encoding
  height, area, or
  volume?
Other Ways To Lie
(with alignment)
  Other Ways To Lie
(with limited context)
  Other Ways To Lie
(with limited context)
  Other Ways To Lie
(with limited context)
  Other Ways To Lie
(with limited context)
  Other Ways To Lie
(with limited context)
Questions?
Questions?
  Design Principles for Graphical Integrity
1. The representation of numbers, as physically measured
   on the surface of the graphic itself, should be directly
   proportional to the numerical quantities represented.
2. 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.
3. Show data variation, not design variation.
4. The number of information-carrying (variable) dimensions
   depicted should not exceed the number of dimensions in
   the data.
5. Graphics must not quote data out of context.
  Design Principles for Graphical Integrity
1. The representation of numbers, as physically measured
   on the surface of the graphic itself, should be directly
   proportional to the numerical quantities represented.
2. 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.
3. Show data variation, not design variation.
4. The number of information-carrying (variable) dimensions
   depicted should not exceed the number of dimensions in
   the data.
5. Graphics must not quote data out of context.
  Design Principles for Graphical Integrity
1. The representation of numbers, as physically measured
   on the surface of the graphic itself, should be directly
   proportional to the numerical quantities represented.
2. 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.
3. Show data variation, not design variation.
4. The number of information-carrying (variable) dimensions
   depicted should not exceed the number of dimensions in
   the data.
5. Graphics must not quote data out of context.
  Design Principles for Graphical Integrity
1. The representation of numbers, as physically measured
   on the surface of the graphic itself, should be directly
   proportional to the numerical quantities represented.
2. 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.
3. Show data variation, not design variation.
4. The number of information-carrying (variable) dimensions
   depicted should not exceed the number of dimensions in
   the data.
5. Graphics must not quote data out of context.
  Design Principles for Graphical Integrity
1. The representation of numbers, as physically measured
   on the surface of the graphic itself, should be directly
   proportional to the numerical quantities represented.
2. 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.
3. Show data variation, not design variation.
4. The number of information-carrying (variable) dimensions
   depicted should not exceed the number of dimensions in
   the data.
5. Graphics must not quote data out of context.
                  Data-Ink




• “Maximize the Data-Ink Ratio”
       The Concept of Data-Ink Ratio



Data-Ink Ratio =
                    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.”
High Data-Ink Ratio Example
Low Data-Ink Ratio Example
           Example Above, Improved

Data-Ink
Ratio of
0.7
      Example Above, Going to Far…

Data-Ink
Ratio of
0.0
              “Within Reason”



• Maximize the Data-Ink Ratio, within reason.

• Erase non-data-ink, within reason.
             Erasing Non-Data-Ink?


• Multiple encodings:
  1.   Height of the left line
  2.   Height of the right line
  3.   Height of shading
  4.   Position of top horizontal line
  5.   Position (placement) of the number
  6.   Value of the number
          Erasing Non-Data-Ink?


• Common statistical graphs
          Erasing Non-Data Ink?


• Symmetry has its values…
Redundancy
                Redundancy

• Making the map into a 24 hour cycle adds
  redundancy, but improves usability
Redundancy
Redundancy
            Application of Editing

• Results of a study
  indicating that one type of
  element always has a
  higher value under
  different experimental
  conditions
           Application of Editing



• After removing all “non-
  data” carrying ink
           Application of Editing



• The Ink that has been
  removed
The Process of Removing
              Another Example


The atomic
volume as a
function of
the atomic
number
Removing Unnecessary Ink
First Insight
Continuing the Removal
                   Problem…


• Removing the connecting lines decreases the
  sense of periodicity…

• Let’s try adding in the grid again to see what
  happens
Redesign, Trial 1
Final Product
Questions?
 Design Principles Based on Data-Ink Ratio


1.   Above all else show the data
2.   Maximize the data-ink ratio
3.   Erase non-data-ink
4.   Erase redundant data-ink
5.   Revise and edit
Questions?
               Assignment 1

• http://www.cs.tufts.edu/comp/150VIZ/

• Due time: Monday January 31st, 2011 at
  midnight.

• Submission process

• A note on presentation
                Assignment 1




• What is a visualization?

				
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