Lecture 06:

Design II

February 5, 2013

COMP 150-2Visualization

Admin

• A2: No need to handle negative values

• Go over the bit shifting and bit masking examples in backbuffer isect example

• Meeting with your TA before the due date of the next assignment!• Liz announcement

• EC1 graded

• Design Lecture by Dan Kass

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

Graphical Excellence

• Tufte’s Principles of Graphical Excellence1. 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 Excellence1. 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 Excellence1. 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 Excellence1. 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 Excellence1. 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 multivariate5. And graphical excellence requires telling the truth about the

data.

Napoleon’s March to Moscow

Minard’s Map ofNapoleon’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?

• 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:

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 line2. Height of the right line3. Height of shading4. Position of top horizontal line5. Position (placement) of the number6. 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 data2. Maximize the data-ink ratio3. Erase non-data-ink4. Erase redundant data-ink5. Revise and edit

Chart Junk

• “Non-data-ink or redundant data-ink”

Discussion

• Why is Chartjunk bad?

• Is it always bad?

Chart Junk vs. Memory

Bateman et al. “Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts”, CHI 2010

Chart Junk vs. Memory

Eye Gaze

Results

Results

Emphasis on Data, Not Graphic

• Don’t do things just because you can. Do them because they are useful.

The Duck!

Questions?