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LibraryThing member detailmuse
According to Edward Tufte, the purpose of graphics is, “Not the complication of the simple; rather (…) the revelation of the complex.” And his The Visual Display of Quantitative Information, first self-published nearly 30 years ago, is now a bible -- a sort of The Elements of Style applied to
Tufte reviews how information can be presented (i.e. a minimal amount via a sentence; a moderate amount via a table; a huge amount via a graphic) and then turns his attention to graphics -- from their beginnings in cartography to how to achieve graphic excellence today.
He urges a multi-disciplinary approach, cautioning that, “Allowing artist-illustrators to control the design and content of statistical graphics is almost like allowing typographers to control the content, style, and editing of prose.” He touches on psychology and cognition. He rails against using graphic design to deceive, and enlightens readers by pulling numerous examples of misrepresentation from prominent media. He devotes a large part of the book to improving the effectiveness of graphs by urging the elimination of “chart junk” (e.g. moiré-effect cross-hatching) and numerous other sources of “non-data ink.” In fact, a chapter wherein he strips away seemingly necessary text, frames, hatch marks, etc. (leaving little more than an ether vapor but in the process simplifying and clarifying the meaning) is revelatory.
So many books I've read recently have referenced Tufte, and I'm glad to have finally read him directly. Highly recommended.
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information graphics.Tufte reviews how information can be presented (i.e. a minimal amount via a sentence; a moderate amount via a table; a huge amount via a graphic) and then turns his attention to graphics -- from their beginnings in cartography to how to achieve graphic excellence today.
He urges a multi-disciplinary approach, cautioning that, “Allowing artist-illustrators to control the design and content of statistical graphics is almost like allowing typographers to control the content, style, and editing of prose.” He touches on psychology and cognition. He rails against using graphic design to deceive, and enlightens readers by pulling numerous examples of misrepresentation from prominent media. He devotes a large part of the book to improving the effectiveness of graphs by urging the elimination of “chart junk” (e.g. moiré-effect cross-hatching) and numerous other sources of “non-data ink.” In fact, a chapter wherein he strips away seemingly necessary text, frames, hatch marks, etc. (leaving little more than an ether vapor but in the process simplifying and clarifying the meaning) is revelatory.
So many books I've read recently have referenced Tufte, and I'm glad to have finally read him directly. Highly recommended.
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LibraryThing member Davidmanheim
"The Visual Display of Quantitative Information" by Edward R. Tufte
Rarely do I find a book that I would call beautiful, but this meets the criteria, both as a physically appealing book, apropos to the purpose of the book, and an informationally dense, and well presented one. A favorite quote of
The book manages to decompose graphical presentation of data into categories other than the x- and y-axes, and instead talks about multifunctional elements and data density. The book reimagines the nature of numerical information using a graphical design perspective, with a healthy dose of common sense as to how graphs are used, and a veritable treasure trove of examples of both good and bad design.
This book, along with "How Buildings Learn," by Stewart Brand, is a rare example of a narrow focus with an incredibly broad appeal. This book is not for the narrow specialist in constructing the sometimes obscurely complex graphics displayed, but rather for anyone who is interested in the data presented to them, and certainly anyone who produces this data in any form.
Rarely do I find a book that I would call beautiful, but this meets the criteria, both as a physically appealing book, apropos to the purpose of the book, and an informationally dense, and well presented one. A favorite quote of
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mine, from Zen and the Art of Motorcycle Maintenance, where the protagonist says; "I remember... remarking about the analytic craftsmanship displayed." This was my reaction to Tufte's book. The book manages to decompose graphical presentation of data into categories other than the x- and y-axes, and instead talks about multifunctional elements and data density. The book reimagines the nature of numerical information using a graphical design perspective, with a healthy dose of common sense as to how graphs are used, and a veritable treasure trove of examples of both good and bad design.
This book, along with "How Buildings Learn," by Stewart Brand, is a rare example of a narrow focus with an incredibly broad appeal. This book is not for the narrow specialist in constructing the sometimes obscurely complex graphics displayed, but rather for anyone who is interested in the data presented to them, and certainly anyone who produces this data in any form.
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LibraryThing member ftorralba
This book has changed the way I judge and make graphical representations of data.
Two lessons emerge from Tufte's masterpiece:
1. Eliminate from a graph anything that doesn't add information
2. Maximize the amount of information per square inch
Don't let the antiquated looks of the book deceive you:
I do wish, however, that this second edition incorporated more advice specific to computer-generated graphics. I'm particularly disappointed because this edition was published as recently as 2001, many years after the personal computer became THE tool for graph making. Without such applied advice, and given the old look of the examples and the large format of the volume, I'm afraid this book will be regarded by many as a geeky coffee-table piece.
Two lessons emerge from Tufte's masterpiece:
1. Eliminate from a graph anything that doesn't add information
2. Maximize the amount of information per square inch
Don't let the antiquated looks of the book deceive you:
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keep reading till the end and you'll find that Tufte's teachings are as valid today as they were 30 years ago.I do wish, however, that this second edition incorporated more advice specific to computer-generated graphics. I'm particularly disappointed because this edition was published as recently as 2001, many years after the personal computer became THE tool for graph making. Without such applied advice, and given the old look of the examples and the large format of the volume, I'm afraid this book will be regarded by many as a geeky coffee-table piece.
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LibraryThing member JBD1
Tufte's classic work on how to (and how not to) present data in visual form. Some good historical examples, well analyzed ... and of course very nicely designed to boot.
LibraryThing member gregorybrown
Edward Tufte's first salvo for sanity in data design. I will admit that I read the book mainly for his historical graph-porn—examples of exemplary works of design and visual analysis. But what ended up being the most enjoyable chapter was when he took some common forms and deconstructed them:
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took them apart, removed the unnecessary pieces, sparingly annotated what was left, and then presented it as an immensely improved graph. While design can churn out results that are best described as magical, it's always great to see the thinking involved, and the skill and process by which something mediocre is slowly shaped into something great. Show Less
LibraryThing member hcubic
This is the first and best of Tufte's volumes on scientific graphics. Not as overpriced as the other ones.
LibraryThing member ilokhov
This book should serve as a great inspiration for anyone who undertakes designing charts or any kind of data visualisation. This is not a technical step-by-step guide for using particular tools or techniques but rather an overview of principles that apply when producing high quality data
Immaculately designed and packed with fantastic illustrations of good and bad approaches to visualisation, this book is a pleasure to read and absorb. I found that it worked well both when reading just a couple of pages at a time and when immersing myself in it for a longer period of time.
This is one of those books that I know I will be revisiting for reference in the future.
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graphics.Immaculately designed and packed with fantastic illustrations of good and bad approaches to visualisation, this book is a pleasure to read and absorb. I found that it worked well both when reading just a couple of pages at a time and when immersing myself in it for a longer period of time.
This is one of those books that I know I will be revisiting for reference in the future.
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LibraryThing member ElizabethPisani
If ever a title did a disservice to a book, this is it. Even I was nearly put off, and I am a data nerd par excellence. This books is fascinating, thought-provoking and very beautiful. Tufte goes on to repeat himself in many subsequent volumes, but this, his first book, says it all.Key concepts:
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ink-to-information ratio, and chart junk. I have plagerised Tufte's ideas and expressions in teaching civil servants and data analysts in countries from Indonesia to Ethiopia. Show Less
LibraryThing member breadhat
Precise, accessible, funny, enlightening, beautiful book. About graphs.
LibraryThing member gottfried_leibniz
This is Classic in the field of Visualization. I highly recommend anyone into UX/UI to go through this book. It's simple read and won't take much time.
Outline:
Part I — Graphical Practice:
1 Graphical Excellence
2 Graphical Integrity
3 Sources of Graphical Integrity and Sophistication
Part
1 - Data Ink and Graphical Redesign
2 – Chart junk: Vibrations, Grids and Ducks
3 - Data Ink Maximization and Graphical Design
4 - Multifunctioning Graphical Elements
5 - Data Density and Small Multiples
6 - Aesthetics and Technique in Data Graphical Design
Part III — Design for Display of Information
1 - Epilogue
Part I — 1) Graphical Practice: Graphical Excellence:
Tufte’s summarizes by saying, it is a matter of substance, statistics, and of design. It gives the viewer the greatest number of ideas in the shortest time with least amount of ink space. It consists of communicating complex ideas communicated with clarify, precision and efficiency.
- It is about clarity in communicating with precision, efficiency that shows data, induce user to think about substance of visualization, avoid distortion, present many numbers in small space, make large datasets coherent, encourage eye to compare various pieces of data, reveal data at several layers of detail, serve clear purpose, be closely integrated with statistical and verbal description of data.
Graphics reveal about data.
-Every Graph or Visualization should let the user to think about the data, not the methodology or technique
-Time Series Data
Two Greatest Scientist of Modern Graphical Design are J.H Lambert, Swiss German Mathematician and William Playfair, Scottish political economist.
Playfair preferred Graphics.
-Descriptive Chronology is not casual expression.
Charles Minard, the French Engineer who explained Napoleon’s army — combination of data-map and time series.
Most Modern Graphics are relational — x, y that encourages to find out casual relationship.
Part 1 — 2) Graphical Practice: Graphical Integrity:
For many of us, we constantly think of lies when we look at a graphic or statistic.
Around 1960, John Turkey made Graphical Practice respectable.
What is distortion in Data Graphic?
Lie Factor = size of effect shown in graphic/ size of effect in data
If it’s greater than 1.05 and less than .95, then it’s substantial
Show data variation not design variation.
Context is important for Graphical Integrity — compared to what?
Lying Graphic cheapen graphical art everywhere.
The Six principles of Graphical Integrity:
- Representation of numbers present in the graphic should be directly proportional to numerical quantities reported
- Clear, detailed and thorough labeling should be used to defeat graphical distortions and ambiguity
- Show data variations, not design variations
- In time series display, use standardized monetary units
- The number of information carrying dimensions should not exceed number of dimensions in data
- Graphics must not quote data out of context
Part 1 —3) Graphical Practice: Sources of Graphical Integrity and Sophistication
Why do they lie?
-Lack of Quantitive skills, the doctrine that statistical data is boring
Many believe that graphics are there to entertain unsophisticated readers. Japan has the highest use of statistical graphics in their newspaper.
Part II — 1) Theory of Data Graphics: Data Ink and Graphical Redesign:
Data Graphics should draw viewers attention to substance of data. It should form quantitive contents.
Fundamental principle is, “Above all else, show the data.” This is the principle for a theory of data graphics.
Data Ink ratio is data ink/total ink used in graphic. Remember to maximize the data ink ratio devoted to the data. Other side of data ink ratio is to erase non-data-ink, within reason.
There’s five principles in theory of data graphics produce substantial changes in graphical design.
-Above all else show the data
-Maximize the data-ink ratio
-Erase non-data-ink
-Erase redundant data-ink
-Revise and edit
Part II — 1) Theory of Data Graphics: Chartjunk, Vibrations, Grids and Duck
Interior decoration of a graphic produces a lot of raw ink that does not tell the viewer anything new. The Grid might include a lot of chart-junk.
When Graphics are taken over design or styles rather than quantitative data, it is called as Big Duck.
Part II — 2) Theory of Data Graphics: Data Ink Maximization and Graphical Design.
Reducing ink ratio in some of the charts might induce changes.
Part II — 3) Theory of Data Graphics: Multifunctioning Graphical Elements
The Same Ink should be used for more than one graphical purpose, it carries data information and performs a design function usually left to non-data-ink. Data based grid is shrewd graphical devise.
Sometimes, the puzzle and hierarchy of multifunctioning graphical elements can data graphics into visual puzzles, crypto graphical mysteries. Colors sometimes generate graphical puzzles. The shades of gray gives us more easier comprehension. This is the key.
Part II — 4) Theory of Data Graphics: Data Density and Small Multiples
How many statistical graphics take advantage of ability to detect large amounts of information in small space? Let’s begin with empirical measure of graphical performance and data density.
Data density of graphic = number of entries in data matrix / area of data graphic
More information is better than less information. Maximize data density and size of data matrix within reason. High volume data must be designed with care. The cost of chart junk, non-data-ink, and redundant data-ink is even more costly in data rich design. We apply shrink principle, which means graphics can be shrunk way down. Bertin’s crisp and elegant line displays small scale graphics in a single page.
Small Multiples, resemble frame of movies, series of graphs, series combination of variables.
A Well designed Small Multiple will contain:
- inevitability comparative
- deftly multivariate
- shrunken high density graphics
- based on large matrix
- drawn exclusively with data ink
- efficient in interpretation
- often narrative in content.
Part III — Theory of Data Graphics: 1) Aesthetic and Technique in Data Graphical Design:
-Graphical Elegance is often found in simplicity of design and complexity of data
Visually attractive graphics gather power from content. Basic structure for showing data are sentence, table and graphic. Often two or three of this should be combined. Make Complexity accessible.
Graphics should prefer towards horizontal, greater in length than height.
Lines in Data Graphic should be thin. Graphical elements look better when their proportions are in balance.
Outline:
Part I — Graphical Practice:
1 Graphical Excellence
2 Graphical Integrity
3 Sources of Graphical Integrity and Sophistication
Part
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II — Theory of Data Graphics: 1 - Data Ink and Graphical Redesign
2 – Chart junk: Vibrations, Grids and Ducks
3 - Data Ink Maximization and Graphical Design
4 - Multifunctioning Graphical Elements
5 - Data Density and Small Multiples
6 - Aesthetics and Technique in Data Graphical Design
Part III — Design for Display of Information
1 - Epilogue
Part I — 1) Graphical Practice: Graphical Excellence:
Tufte’s summarizes by saying, it is a matter of substance, statistics, and of design. It gives the viewer the greatest number of ideas in the shortest time with least amount of ink space. It consists of communicating complex ideas communicated with clarify, precision and efficiency.
- It is about clarity in communicating with precision, efficiency that shows data, induce user to think about substance of visualization, avoid distortion, present many numbers in small space, make large datasets coherent, encourage eye to compare various pieces of data, reveal data at several layers of detail, serve clear purpose, be closely integrated with statistical and verbal description of data.
Graphics reveal about data.
-Every Graph or Visualization should let the user to think about the data, not the methodology or technique
-Time Series Data
Two Greatest Scientist of Modern Graphical Design are J.H Lambert, Swiss German Mathematician and William Playfair, Scottish political economist.
Playfair preferred Graphics.
-Descriptive Chronology is not casual expression.
Charles Minard, the French Engineer who explained Napoleon’s army — combination of data-map and time series.
Most Modern Graphics are relational — x, y that encourages to find out casual relationship.
Part 1 — 2) Graphical Practice: Graphical Integrity:
For many of us, we constantly think of lies when we look at a graphic or statistic.
Around 1960, John Turkey made Graphical Practice respectable.
What is distortion in Data Graphic?
Lie Factor = size of effect shown in graphic/ size of effect in data
If it’s greater than 1.05 and less than .95, then it’s substantial
Show data variation not design variation.
Context is important for Graphical Integrity — compared to what?
Lying Graphic cheapen graphical art everywhere.
The Six principles of Graphical Integrity:
- Representation of numbers present in the graphic should be directly proportional to numerical quantities reported
- Clear, detailed and thorough labeling should be used to defeat graphical distortions and ambiguity
- Show data variations, not design variations
- In time series display, use standardized monetary units
- The number of information carrying dimensions should not exceed number of dimensions in data
- Graphics must not quote data out of context
Part 1 —3) Graphical Practice: Sources of Graphical Integrity and Sophistication
Why do they lie?
-Lack of Quantitive skills, the doctrine that statistical data is boring
Many believe that graphics are there to entertain unsophisticated readers. Japan has the highest use of statistical graphics in their newspaper.
Part II — 1) Theory of Data Graphics: Data Ink and Graphical Redesign:
Data Graphics should draw viewers attention to substance of data. It should form quantitive contents.
Fundamental principle is, “Above all else, show the data.” This is the principle for a theory of data graphics.
Data Ink ratio is data ink/total ink used in graphic. Remember to maximize the data ink ratio devoted to the data. Other side of data ink ratio is to erase non-data-ink, within reason.
There’s five principles in theory of data graphics produce substantial changes in graphical design.
-Above all else show the data
-Maximize the data-ink ratio
-Erase non-data-ink
-Erase redundant data-ink
-Revise and edit
Part II — 1) Theory of Data Graphics: Chartjunk, Vibrations, Grids and Duck
Interior decoration of a graphic produces a lot of raw ink that does not tell the viewer anything new. The Grid might include a lot of chart-junk.
When Graphics are taken over design or styles rather than quantitative data, it is called as Big Duck.
Part II — 2) Theory of Data Graphics: Data Ink Maximization and Graphical Design.
Reducing ink ratio in some of the charts might induce changes.
Part II — 3) Theory of Data Graphics: Multifunctioning Graphical Elements
The Same Ink should be used for more than one graphical purpose, it carries data information and performs a design function usually left to non-data-ink. Data based grid is shrewd graphical devise.
Sometimes, the puzzle and hierarchy of multifunctioning graphical elements can data graphics into visual puzzles, crypto graphical mysteries. Colors sometimes generate graphical puzzles. The shades of gray gives us more easier comprehension. This is the key.
Part II — 4) Theory of Data Graphics: Data Density and Small Multiples
How many statistical graphics take advantage of ability to detect large amounts of information in small space? Let’s begin with empirical measure of graphical performance and data density.
Data density of graphic = number of entries in data matrix / area of data graphic
More information is better than less information. Maximize data density and size of data matrix within reason. High volume data must be designed with care. The cost of chart junk, non-data-ink, and redundant data-ink is even more costly in data rich design. We apply shrink principle, which means graphics can be shrunk way down. Bertin’s crisp and elegant line displays small scale graphics in a single page.
Small Multiples, resemble frame of movies, series of graphs, series combination of variables.
A Well designed Small Multiple will contain:
- inevitability comparative
- deftly multivariate
- shrunken high density graphics
- based on large matrix
- drawn exclusively with data ink
- efficient in interpretation
- often narrative in content.
Part III — Theory of Data Graphics: 1) Aesthetic and Technique in Data Graphical Design:
-Graphical Elegance is often found in simplicity of design and complexity of data
Visually attractive graphics gather power from content. Basic structure for showing data are sentence, table and graphic. Often two or three of this should be combined. Make Complexity accessible.
Graphics should prefer towards horizontal, greater in length than height.
Lines in Data Graphic should be thin. Graphical elements look better when their proportions are in balance.
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LibraryThing member Harlan879
I was a little disappointed in this classic work on charts and graphs. On the one hand, it was clearly a revolutionary kick in the pants to a field that had no prior organization. On the other hand, as a person who makes charts and graphs as a regular part of his work (academic researcher), I found
Perhaps his later work is more useful. I'll have to check it out and see.
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some of the advice to be misguided. His efforts to redesign clunky box plots, although admirable, end up with not *enough* ink. The little offset lines to indicate quartile ranges are just silly. And for someone who talks about the data being much more important than the design, he barely talks about data at all. Perhaps his later work is more useful. I'll have to check it out and see.
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LibraryThing member maryh10000
If you make presentations of data to people, you must read this.
LibraryThing member HoraceSPatoot
A great many endeavors depend on communication. A very efficient way to communicate is through graphs. We spend much time in school learning to interpret graphs, but very little time learning how to create graphs that communicate clearly and efficiently. Tufte fixes all of that. In an odd way, this
I used to spend a lot of time building ducks. Now I spend as much time destroying ducks. Read, and you'll understand what I mean.
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is a life changing book -- not in a philosophical sense but in a very practical sense. I used to spend a lot of time building ducks. Now I spend as much time destroying ducks. Read, and you'll understand what I mean.
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LibraryThing member jamespurcell
Excellent and innovative reference for visual displays.
LibraryThing member EowynA
This is sensible, artistic advice about displaying statistics in a clear, understandable manner. I've been wondering about the bar graphs in the Book -- are they displaying my little bits of information in a clear, unambiguous, and effective manner? Turns out they are okay, but can be improved. So
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they will be, in accordance with this excellent analysis of using design to maximize communication. Highly recommended. Show Less
LibraryThing member alspray
“Visual Display…” has my minimalist self at odds with my usability self. I find Tufte’s approach quite compelling …though perhaps sometimes it goes a little (eensy weensy) too far. As in, some of his pinnacle examples left me quite befuddled. All in all though, another gorgeous production
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by Tufte with a plethora of rich examples to explore. I wish I could frame every page and hang on it on the wall. Show Less
LibraryThing member alv
Very well written and considerably helpful. Carefully edited. Some of the exemplary diagrams are faulty in other, previously identified ways. And too much respect is paid to the figure of Playfair, sometimes leaning on an implicit argument by authority (e.g. aspect ratio). Healthy questioning of
Please comment in my profile if you know of software tools that support directly or indirectly the principles advocated by Tufte.
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fundamental truths and necessary praise of information density in an age of visual dumbing-down. Helps avoid limiting creativity in graphical design because of constraining tools. Please comment in my profile if you know of software tools that support directly or indirectly the principles advocated by Tufte.
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LibraryThing member Murdocke23
This first Tutfe book focuses on charts and graphs. The text is insightful but could be presented more simply, but the ideas and examples around information graphics are excellent. Shares some similar concepts from Envisioning Information and Visual Explanations.
LibraryThing member KirkLowery
The best. If you use graphics in writing, you must read Tufte.
LibraryThing member jontseng
Like many "cult" books, its genius is making and obscure subject utterly fascinating. Contains a number of iconic images, particularly the graphic of Napoleon's retreat from Moscow.
LibraryThing member MarkGFaust
Absolutely essential for anyone who needs to present information in a coherent, easily understood way.
LibraryThing member lorin
I had heard many people rave about this book, and after I read it I realized that it deserved the hype. The book is a discussion on the best way to present data sets to an audience through the use of charts and graphics. It's something that's really essential to scientists and engineers, and yet we
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receive no real training in it, which is a shame. Tufte's book is a setp in the right direction. Show Less
LibraryThing member hblanchard
Required reading for visual designers, statisticians, graphic designers, scientists, researchers, engineers, human factors professionals, human computer interaction designers, mathematicians, journalists ... oh heck, required reading for everybody.
LibraryThing member Cheryl_in_CC_NV
recommended by xkcd
Read/ scanned in just a few days, because a fair bit was over my head. The parts I did understand, however, were terrific and valuable, both for readers and creators of graphs and tables.
Tufte has a sense of humor, too. When showing how graphs can be presented to be misleading
I would *love* to take a course under Tufte, or even under any decent professor who uses this book as the primary text.
If your library has this, I highly recommend you at least browse it."
Read/ scanned in just a few days, because a fair bit was over my head. The parts I did understand, however, were terrific and valuable, both for readers and creators of graphs and tables.
Tufte has a sense of humor, too. When showing how graphs can be presented to be misleading
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(ie, making a bar graph meant to represent gains vs losses start at a large negative number, and disguising the numbers by having a bold 'background' illustration), he quantifies the apparent discrepancy as a lie factor."I would *love* to take a course under Tufte, or even under any decent professor who uses this book as the primary text.
If your library has this, I highly recommend you at least browse it."
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LibraryThing member datrappert
If you like numbers and graphs, this will put you in heaven. More importantly, it will make you think about the best ways to display data and look at every data graphic in a newspaper or magazine with a new, highly critical eye.
Publication
Cheshire, Conn. : Graphics Press, c2001.
Description
This book deals with the theory and practice in the design of data graphics and makes the point that the most effective way to describe, explore, and summarize a set of numbers is to look at pictures of those numbers, through the use of statistical graphics, charts, and tables. It includes 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Also offered is information on the design of the high-resolution displays, small multiples, editing and improving graphics, and the data-ink ratio. Time-series, relational graphics, data maps, multivariate designs, as well as detection of graphical deception: design variation vs. data variation, and sources of deception are discussed. Information on aesthetics and data graphical displays is included. The 2nd edition provides high-resolution color reproductions of the many graphics of William Playfair (1750-1800), adds color to other images where appropriate, and includes all the changes and corrections during the 17 printings of the 1st edition.… (more)
Original publication date
1983
2001 (2nd Ed.)
Physical description
197 p.; 28 cm