Visual Explanations

Edward Tufte har skrive fire bøker om informasjonsdesign:

1983: The Visual Display of Quantitative Information
1990: Visual Explanations: Images and Quantities, Evidence and Narrative
1990: Envisioning Information
2006: Beautiful Evidence

I Visual Explanations: Images and Quantities, Evidence and Narrative viser, diskuterar og analyserar Tufte eksempel på god og dårlig informasjonsdesign. Han peikar på feil og styrkjer ved ulike visuelle framstillingar. Boka er ei øving i kritisk tenking, og handlar om korleis fortelje sanninga og fjerne alle hinder for forståelse mellom designeren og lesaren. Eg saknar å kunne lese om Tufte sin eigen designprosess, det hadde vore fint å vite meir om korleis han har kome fram til konklusjonane. Sjølve boka er også flott, eg likar spesielt den lille detaljen kor ord og symbol som vert henta frå visuelle eksempel og satt inn i teksten får beholde det originale skriftsnittet – lett å finne igjen både frå eksempel til tekst og tekst til eksempel.

Eg noterte ned undervegs nokre småting som eg ynskjer å hugse i framtida:

  • Good design brings absolute attention to data and should take into account how, when, and where the information is used.
  • The heart of information design is to document and explain a process, to make verbs visible.
  • The deep, fundamental question in statistical analysis is “Compared with what?” Comparison exaggerate the impact.
  • Repeated variations on the same theme will often clarify and develop an idea.
  • Many times size is an expressive factor – use a constant scale (consistent relative scale throughout an entire set, ex. Malevich “0-10”).
  • Computer visualizations: remember to show scale, orientation and labels.
  • Questions to ask yourself when you make a model: How many? How often? Where? How much? At what rate?
  • When assessing evidence, it is helpful to see a full data matrix, all observations for all variables, those private numbers from which the public displays are constructed. No telling what will turn up.
  • Information displays should serve the analytic purpose at hand; if the substantive matter is a possible cause-effect relationship, then graphs should organize data so as to illuminate such a link.
  • The test of all information design, the integrity of the content displayed: Is the display revealing the truth? Is the representation accurate? Are the data carefully documented? Do the methods of display avoid spurious readings of the data? Are appropriate comparisons and contexts shown?
  • Follow the design strategy of the smallest effective difference: make all visual distinctions as subtle as possible, but still clear and effective. Use just notable differences, visual elements that make a clear difference but no more – contrasts that are definite, effective and minimal. Minimal differences allow more differences. This helps in designing the various secondary and structural elements in displays of information – muting the secondary elements will often reduce visual clutter – and thus help to clarify the primary information.
  • It is best to avoid designs involving icons and symbols – be simple and clear!
  • Parallelism connects visual elements (position, orientation, overlap, synchronization and similarities in content). Congruity of structure across multiple images gives the eye a context for assessing data variation. Parallelism is not simply a matter of design arrangements, for the perceiving mind itself actively works to detect and indeed to generate links, clusters, and matches among assorted visual elements.
  • Codes obstruct parallelism; replacing codes with direct labels unifies the information.
  • Multiple images reveal repetition and change, pattern and surprise – the defining elements in the idea of information – multiples directly depict comparisons, the essence of statistical thinking. Multiples create visual lists of objects and activities, nouns and verbs, helping viewers to analyze, compare, differentiate, decide. Multiples amplify, intensify, and reinforce the meaning of images.

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