Visual Explanations: Images and Quantities, Evidence and Narrative by Edward Tufte


  1. This book describes design strategies – the proper arrangement in space and time of images, words, and numbers – for presenting information about motion, process, mechanism, cause and effect. These strategies are found again and again in portrayals of explanations, quite independent of the particular substantive content or technology of display.

Key Takeaways

  1. The first part of this book examines the logic of depicting quantitative evidence. What principles should inform our designs for showing data? Where do those principles come from? How can the integrity of quantitative descriptions be maintained in the face of complex and animated representations of data? What are the standards for evaluating visual evidence, especially for making decisions and reaching conclusions? The second part considers design strategies, often for the arrangement of images as narrative. Here the issues are more visual – and lyrical – than quantitative. The idea is to make designs that enhance the richness, complexity, resolution, dimensionality, and clarity of the content. By extending the visual capacities of paper, video, and computer screen, we are able to extend the depth of our own knowledge and experience. And so this part of the book reports on architectures of comparison and narrative: parallelism, multiples, and confections
  2. Those who discover an explanation are often those who construct its representation
    1. Hologram in the head, Wozniak designing both the hardware and the software – no bugs ever found 
  3. Many of our examples suggest that clarity and excellence in thinking is very much like clarity and excellence in the display of data. When principles of design replicate principles of thought, the act of arranging information becomes an act of insight
  4. My 3 books on information design stand in the following relation:
    1. The Visual Display of Quantitative Information is about pictures of numbers, how to depict data and enforce statistical honesty
    2. Envisioning Information is about pictures of nouns (maps and aerial photographs, for example, consist of a great many nouns lying on the ground). Envisioning also deals with visual strategies for design: color, layering, and interaction effects
    3. Visual Explanations is about pictures of verbs, the representation of mechanism and motion, of process and dynamics, of causes and effects, of explanation and narrative. Since such displays are often used to reach conclusions and make decisions, there is a special concern with the integrity of the content and the design
    4. These books are meant to be self-exemplifying: the objects themselves embody the ideas written about. Enchanted by the elegant and precise beauty of the best displays of information, and also inspired by the idea of self-exemplification, I have come to write, design, and publish the 3 books myself.
      1. Godel and recursion
  5. Clear logic of data display and analysis includes:
    1. Placing the data in an appropriate context for assessing cause and effect
    2. Making quantitative comparisons. The deep, fundamental question in statistical analysis is compared to what? Therefore, investigating the experiences of the victims of cholera as Snow did is only part of the search for credible evidence; to understand fully the cause of the epidemic also requires an analysis of those who escaped the disease. With great clarity, the map presented several intriguing clues for comparisons between the living and the dead, clues strikingly visible at a brewery and work-house…
    3. Considering alternative explanations and contrary cases. Sometimes it can be difficult for researchers – who both report and advocate their findings – to face up to threats to their conclusions, such as alternative explanations and contrary cases. Nonetheless, the credibility of a report is enhanced by a careful assessment of all relevant evidence, not just evidence overtly consistent with explanations advanced by the report. The point is to get it right, not to win the case, not to sweep under the rug all the assorted puzzles and inconsistencies that frequently occur in collections of data
    4. Assessment of possible errors in the numbers reported in the graphics. Snow’s analysis attends to the sources and consequences of errors in gathering the data. In particular, the credibility of the cholera map grows out of supplemental details in the text – as image, word, and number combine to present the evidence and make the argument. Detailed comments on possible errors annotate both the map and the table, reassuring readers about the care and integrity of the statistical detective work that produced the data graphics
      1. Enough exploration must be done so that the results are shown to be relatively insensitive to plausible alternative specifications and data choices. Only in that way can the statistician protect himself or herself from the temptation to favor the client and from the ensuring cross-examination. – John Tukey
  6. Numbers become evidence by being in relation to
  7. Chartjunk – good design brings absolute attention to data
  8. Jonson’s Principle – these problems are more than just poor design, for a lack of visual clarity in arranging evidence is a sign of a lack of intellectual clarity in reasoning about evidence.
  9. Visual representations of evidence should be governed by principles of reasoning about quantitative evidence. For information displays, design reasoning must correspond to scientific reasoning. Clear and precise seeing becomes as one with clear and precise thinking.
  10. To document and explain a process, to make verbs visible, is at the heart of information design
  11. Presenting Techniques
    1. These techniques of disinformation design [magic], when reversed, reinforce strategies of presentation used by good teachers. Your audience should know beforehand what you are going to do; then they can evaluate how your verbal and visual evidence supports your argument. And so we have some practical advice for giving a talk or paper:
      1. Near the beginning of your presentation, tell the audience: what the problem is, why the problem is important, what the solution to the problem is.
      2. If a clear statement of the problem cannot be formulated, then that is a sure sign that the content of the presentation is deficient. Repeated variations on the same idea will often clarify and develop an idea.
    2. To explain complex ideas, use the method of PGP: Particular – General – Particular
      1. Seek to maximize the rate of information transfer to your audience. Yet many presentations rely on low-resolution devices to communicate information – reading aloud from images projected up on the wall from computer screens or from the dreaded overhead projector, or talk talk talk. Instead, try a high-resolution method: No matter what, give everybody in the audience one or more pieces of paper, packed with material related to your presentation. Handouts show pictures, diagrams, data tables, research methods, references, names of people at the meeting, or the complete text of the paper outlined in your talk. Unlike evanescent projected images, permanent and portable paper has credibility. Paper serves as a testimonial record documenting your talk, letting your audience know that you take responsibility for what you say. People can file your handouts away and then come back in a month and ask, “Didn’t you say this?”
    3. Analyze the details of your presentation; then master those details by practice, practice, practice
    4. Show up early. Something good is bound to happen
    5. Finish early
  12. Questions to ask about your data/presentation
    1. Is the display revealing the truth?
    2. Is the representation accurate?
    3. Are the data carefully documented?
    4. Do the methods of display avoid spurious readings of the data?
    5. Are appropriate comparisons and contexts shown?
  13. The smallest effective difference
    1. Make all visual distinctions as subtle as possible, but still clear and effective. Relevant to nearly every display of data, the smallest effective difference is the Occam’s razor (“what can be done with fewer is done in vain with more”) of information design. And often the happy consequence of an economy of means is a graceful richness of information, for small differences allow more differences. 
    2. Minimal distinctions reduce visual clutter. small contrasts work to enrich the overall visual signal by increasing the number of distinctions that can be made within a single image; thus design by means of small effective differences helps to increase the resolution of our images. 
  14. Parallelism
    1. Embodying inherent links and connections, parallelism synchronizes multiple channels of information, draws analogies, enforces contrasts and comparisons. Our examples have inventoried all sorts of design strategies that collate like with like: pairing, orientation, simultaneity, overlap, superimposition, flowing together on a common track, codes, pointer lines, sequence, adjacency, analogy, similar content. Parallelism provides a coherent architecture for organizing and learning from images – as well as from words and numbers, the allies of images. And by establishing a structure of rhythms and relationships, parallelism becomes the poetry of visual information. 
  15. Multiples in space and time
    1. 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 enhance the dimensionality of the flatlands of paper and computer screen, giving depth to vision by arraying panels and slices of information. Multiples create visual lists of objects and activities, nouns and verbs, helping viewers to analyze, compare, differentiate, decide – as we see below with 12 hands in 12 positions for making 12 sounds. Multiples represent and narrate sequences of motion. Multiples amplify, intensify, and reinforce the meaning of images.
    2. Multiples help to monitor and analyze multi-variable processes – ordinary occurrences in medicine, finance, quality control, and large-scale industrial and engineering operations. By providing a quick, simultaneous look at a continuing flow of different measurements, multiples help sort out the relevant substance from a flood of numbers.

What I got out of it

  1. Another beautiful book by Tufte with some great advice on how to present quantitative evidence.