Graphical excellence
complex ideas communicated with clarity, precision and efficiency.
that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the shortest space
graphical excellence is nearly always multivariate
And graphical excellence requires telling the truth about the data
Data-Built data measures
Using the data itself to plot data “increases the quantitative detail and dimensionality of a graphic”
If we are going to make a mark it may as well be a meaningful one. The simplest—and most useful—meaningful mark is a digit. (Tukey)
Examples:
- stem-and-leaf
- “Living histograms”
- Complex data measure encodings, e.g. plot of Chernoff faces
Color guidance
Color often generates graphical puzzles. Despite our experiences… the mind’s eye does not readily give a visual ordering to colors.
Greyscale shades show varying quantities better than color.
Multiple layers of information
- What is seen from a distance, an overall structure usually aggregated from an underlying microstructure.
- What is seen up close and in detail, the fine structure of the data
- What is seen implicitly underlying the graphic
Consider the viewing architecture of a graphic.
Data-ink ratio
Data-ink is the non-erasable core of a graphic, the non-redundant ink arranged in response to variation in the numbers represented.
Whitespace
Even part of the data measures can be erased, making a white grid
range-frame
the frame of a graphic can become an effective data-communicating element simply by erasing part of it.
should extend only to the measured limits of the data
Data density
Taking into account the size of the graphic in relation to the amount of data displayed yields the data density: