1. “The greatest value of a picture is when it focuses us to notice what we have never expected to see” – John W. Tukey
Studies have shown that 8% of men and 0.5%
of women have color vision deficiency. For
such reasons it is often suggested not to use
red & green together. For example in the chart
below color is the main distinguishing
parameter to separate a good square from bad
square.
Contrast and analogy are the principles that
define color design. Contrast draws
attention, analogy groups. In the above
figure the contrasting red squares stand out
from the field of analogous blue-green ones
and capture the attention.
But if the colors are used stand alone. For
example in two different chart below, one
red and one green and they are labeled
well, then these two colors can be used
together.
Color selection in data visualization is not
merely an aesthetic choice. It depends on the
type of data being considered:
• Sequential color scheme can be used to
organize quantitative data from high to low
using a gradient effect.
• Diverging color scheme can be used to
highlight the middle range/extremes of
quantitative data by using two contrasting
hues on the extremes and a lighter tinted
mixture to highlight the middle range.
•Qualitative color schemes can be used to
highlight qualitative categories. With
qualitative data, we would want to create a
lot of contrast, using different hues to
represent each of your data points.
Color usage guidelines often include a
statement like, "Pure blue should not be used
for fine detail or background". The black text
on the pure blue background and pure blue
text on the black background are barely legible
at any size [Illustrated Image below]. Legibility
is particularly poor at the smallest font sizes.
This happens because Blue has low luminance.
Variation in luminance can also be used to
separate overlaid values into layers, where
low contrast layers can sit behind high
contrast ones without causing
visual clutter. Figure below demonstrates
this principle, and the fact that contrast in
hue does not create this separation.
When there is sufficient luminance contrast,
however, as in the below blue/white panels,
blue is a usable label color even at the
smallest font sizes.
Figure:(Left) The overlaid black text is difficult
to read; (center) Creating three different levels
of contrast separates the information; (right)
Using three different hues does not. (Larry
Arend, NASA)
Data Visualization useful tips :
• Keep it simple – Always choose the simplest way to convey
information
• Have a specific message to communicate
• Select the right chart form based on the data and know its
strength and limits
• Use compelling headlines and decks to describe the take away
message of the visualization.
• Maximize the data-ink ratio(Edward Tufte)
• Avoid using special effects, such as 3D graphics. Sometimes the
perspective added in the 3D graphics distorts the data and makes
it difficult to interpret
• Add hierarchy to the data – Data should have an order of
importance.
Reference Links:
https://www.idrc.ca/sites/default/files/sp/Documents%20EN/Quick-tips-English-22-May-2012.pdf
https://www.perceptualedge.com/articles/b-eye/choosing_colors.pdf
http://img.labnol.org/di/data-chart-type.png
http://blog.hubspot.com/marketing/color-combination-data-visualization#sm.0017tgp1t1a98d8dwp62nwh0zj768
Created by: Sneha Nath, Sept 2016
Department: R&D IT IDIA