Posts Tagged “tufte”
Nov 10, 2011
These are my notes about “Envisioning information” by Edward R. Tufte. It’s not a normal summary because most of the content needs the graphics, plots and figures being discussed. The following notes cover the whole book (six chapters).
EDIT: Manuela wrote another, easier to read summary.
The methods in this book work to increase the number of dimensions that can be represented on plane surfaces and the data density. Nearly every escape from flatland demands an extensive compromise, trading off one virtue against another. Even our language often lacks capacity to communicate a sense of dimensional complexity. Some design strategies are found again and again (examples of over 380 years of sunspot data analysis). These design strategies are surprisingly widespread, albeit little appreciated, and occur independently of the content of the data.
Massive Java railroad line example on p. 24-25. The train diagonals cleverly multiple-function, recording six variables at once (p. 26). Example of criminal activity for a trial on p. 30-31. The chart invites reading both horizontally and vertically. The eyes detect curious patterns, which make these displays persuasive and memorable. Visual displays of information encourage a diversity of individual viewer styles and rates of editing, personalising, reasoning and understanding. Unlike speech, visual displays are simultaneously a wideband and a perceiver-controllable channel.
We envision information to reason about, communicate, document and preserve that knowledge. Chartjunk on p.34: data-thin, uncontextual graphs. Its promoters imagine numbers to be dull and tedious, requiring ornament. If numbers are boring, you got the wrong numbers. The audience might be busy or eager to get on with it, but not stupid. Chartjunk looks more like a poster, meant to be looked at from a distance (thin data density).
Detail cumulates in coherent structures. Simplicity of reading derives from the context of detailed and complex information, properly arranged. To clarify, add detail. Stem-and-leaf plots of statistical analysis also rely on micro/macro design (examples on p. 46-47).
We thrive in information-thick worlds because of our marvellous and everyday capacities to select, edit, single out, structure, highlight, group, … Visual displays rich with data are not only an appropriate and proper complement to human capabilities, but also such designs are frequently optimal. If the visual task is contrast, comparison and choice, then the more relevant information within eyespan, the better. Low-density requires visual memory, a weak skill. High density also allows viewers to select, narrate, recast and personalise data for their own uses.
What about information overload? The question misses the point. Clutter and confusion are failures of design, not attributes of information. Interesting quote on typography on p. 51. The deepest reason for displays that portray complexity and intricacy is that the worlds we seek to understand are complex and intricate.
Layering and separation
This technique is one the most powerful devices for reducing noise and enriching the content of displays. The various elements interact, creating non-information patterns and texture simply through their combined presence (1 + 1 = 3 or more). Colour effortlessly differentiates between annotation and annotated (example on p. 54). What matters is the proper relationship among information layers (example of old + improved design on p. 54-55). For tables, try to do without rules altogether, only use when absolutely necessary. Example of map (good and bad) on p. 58. Example of (non-)dull background on p. 59. Notes on how 1 + 1 = 3 can also be applied to noise on p. 61-62. Example of use of colours (another bad + good design) on p. 63.
Information consists of differences that make a difference. A fruitful method for the enforcement of such differences is using layering and separation.
Quantitative reasoning is based on “compared to what?”. Small multiples answer by visually enforcing comparisons of changes, of the differences among objects, and the scope of alternatives. Information slices are positioned within the eyespan, so that viewers make comparisons at a glance. Example of drawing a Kana character on p. 69. Simultaneous two-dimensional indexing of the multiplied image, flatland within flatland, significantly deepens displays with little added complication in reading.
Colour and information
Example of Swiss mountain map on p. 80. Fundamental uses of colour in information design: label (colour as noun), measure (as quantity), represent or imitate reality (representation), enliven or decorate (beauty). Principles to minimise colour damage: (1) pure, bright colours have loud, unbearable effects when they stand unrelieved over large areas adjacent to each other, but can work very well when used sparingly on or between dull background tones; (2) placing of light, bright colours mixed with white next to each other usually produces unpleasant results, esp. if the colours are used for large areas; (3) large area background or base-colours should do their work most quietly, allowing the smaller, bright areas to stand out most vividly (strongly muted colours, mixed with grey, provide the best background for the coloured theme).
What palette of colours should we choose to represent and illuminate information? Use colours in nature (familiar and coherent, possessing a widely accepted harmony to the human eye), esp. those on the lighter side such as blues, yellows, and greys of sky and shadow. Great examples on p. 90.
In the ocean map, quantities are shown by a value scale, progressing from light to dark blue. Colour rainbows confuse viewers to mumbling colour names and the numbers they represent (“To see is to forget the name of the thing one sees”). Colours are sensitive to context. In the ocean map, contours (which are very helpful) are labelled with depth measurements. Edge lines allow very fine value distinctions, increasing scale precision. Example of bad map/good colour on maps on p. 94-95.
Narratives of space and time
Example of bad/good train schedule on p. 104-105. Space-time grids have a natural universality, with nearly boundless subtleties and extensions. Great, assorted examples on p. 110-111. Example of “tale of two cities” on p. 112-113.
I’m aware that this summary is not very useful if you can’t see the different diagrams being examined, but it’s partly for myself :-) Anyway, if you like the ideas in the book, go buy it, it’s a great book in a big format, with really nice paper and full of very interesting examples of both good and bad information design.