Information Design & Data Visualization
No more LittleDataGraphics
Small data sets should be shown directly...LittleDataGraphics (pie charts, bar charts) translate and encode data into areas and colors. Viewers must then mentally translate codes back into numbers. These codes are unique to the local sets of data graphics, and do not repay learning. Instead, just directly show numbers as numbers. No more LittleDataGraphics. Data visualizations are at their best when there is so much data that the only way to see it...is to see it.
The Visual Information Seeking Mantra
There are many visual design guidelines but the basic principle might be summarized as the Visual Information Seeking Mantra:
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demand
Overview first, zoom and filter, then details-on-demandEach line represents one project in which I found myself rediscovering this principle and therefore wrote it down it as a reminder. It proved to be only a starting point in trying to characterize the multiple information visualization innovations occurring at university, government, and industry research labs.
Envisioning Information
A Book by Edward TufteBeautiful Evidence
A Book by Edward TufteThe Visual Display of Quantitative Information
A Book by Edward TufteThe Elements of Graphing Data
A Book by William S. ClevelandVision Science
A Book by Stephen E. PalmerVisual Explanations
A Book by Edward TufteVisualizing Algorithms
An Article by Mike BostockInformation Visualization: Perception for Design
A Book by Colin WareThe Eyes Have It
A Research Paper by Ben ShneidermanVisualizing Data
A Book by William S. ClevelandExploratory Data Analysis
A Book by John TukeyPlus Equals #4
An Article by Rob WeychertOne of the seeds for Plus Equals was planted a few years ago with Incomplete Open Cubes Revisited, my extension of a Sol LeWitt work. I learned a lot about isometric projection from that project, but my affection for the concept didn’t begin there. Whether I’m looking at a Chris Ware illustration or an exploded-view technical drawing of a complex machine, an isometric rendering always stirs something in me.
In search of visual texture
An Article by Rachel PruddenI’m now more inclined to attribute Looseleaf’s power to its visual texture than to some cognitive media-style abstraction. And the visual texture owes more to the beauty (yes, beauty!) of the original pdfs from the Vasulka Archive. Perhaps the demo is best understood not as a prototype generic tool, but as a specific curated experience in its own right, with form and content claiming equal importance in its overall success.
Even so, I think there are some general lessons that can be drawn from this demo:
- Content is not inert
- Visual texture lets content breathe
- Visual texture lets the eye wander without losing itself
Chartwell
A FontThis set of tools for easily creating graphs is conveniently disguised as a set of fonts. OpenType features are used to interpret and visualize the data. The data remains as editable text, allowing for painless updates.
Windy
A WebsiteBetter colormaps?
An Article by Mark LibermanA modest sample of alternative ways of coloring the same type of 2-D density plots of rates of F0 change and amplitude change.
ImageQuilts
A Tool by Edward Tuftepress.stripe.com
A WebsiteStripe partners with millions of the world’s most innovative businesses. These businesses are the result of many different inputs. Perhaps the most important ingredient is “ideas.”
Stripe Press highlights ideas that we think can be broadly useful. Some books contain entirely new material, some are collections of existing work reimagined, and others are republications of previous works that have remained relevant over time or have renewed relevance today.
Between the Words
An Artwork by Nicholas RougeuxMoby Dick.
Between the Words is an exploration of visual rhythm of punctuation in well-known literary works. All letters, numbers, spaces, and line breaks were removed from entire texts of classic stories...leaving only the punctuation in one continuous line of symbols in the order they appear in texts. The remaining punctuation was arranged in a spiral starting at the top center with markings for each chapter and classic illustrations at the center.
SeriesHeat
A Website by Jim VallandinghamSearch for a TV Series to see a heatmap of average IMDb ratings for each episode.
Time-based analytics
An Article by Ryan SingerAnalytics apps don't tell you much about usage behavior. You might be able to see how many users performed an event, or how many times they did it. But none of the analytics packages out there are good at showing you how often people do things. Are they using to-dos once a week? Every day? Only signing into the app once a month but happily paying for years?
Time matters. You can't understand usage without time.
Cameras and lenses
An Article by Bartosz CiechanowskiPictures have always been a meaningful part of the human experience. From the first cave drawings, to sketches and paintings, to modern photography, we’ve mastered the art of recording what we see.
Cameras and the lenses inside them may seem a little mystifying. In this blog post I’d like to explain not only how they work, but also how adjusting a few tunable parameters can produce fairly different results.
The Subtleties of Color
A Series by Robert SimmonThe use of color to display data is a solved problem, right? Just pick a palette from a drop-down menu (probably either a grayscale ramp or a rainbow), set start and end points, press “apply,” and you’re done. Although we all know it’s not that simple, that’s often how colors are chosen in the real world. As a result, many visualizations fail to represent the underlying data as well as they could.
tixy.land
A Websitesin(t * x) * cos(t * y)
Creative code golfing.
Zipdecode
A Website by Ben FryA Library Demand List
A Website by Robin SloanThis visualization takes the current New York Times Best Sellers list for combined print and e-book fiction and scales each title according to the demand for its e-book edition at a collection of U.S. public libraries, selected for their size and geographic diversity.
MIT Student Hub
An Article by Alex HogrefeThe project is located on the MIT Campus and will be a “Student Hub” containing restaurants, large event spaces, and smaller study spaces.
V-RESAS
An ApplicationAll in & with the flow
An Article by Buster BensonInfoCrystal
A Research PaperThis paper introduces a novel representation, called the InfoCrystal, that can be used as a visualization tool as well as a visual query language to help users search for information. The InfoCrystal visualizes all the possible relationships among N concepts.
Readings in Information Visualization: Using Vision to Think
A Book by Ben Shneiderman
What 80% Comprehension Feels Like
One of the major principles of extensive reading is that if a learner can comprehend material at 98% comprehension, she will acquire new words in context, in a painless, enjoyable way. But what is 98% comprehension?
98% comprehension
You live and work in Tokyo. Tokyo is a big city. More than 13 million people live around you. You are never borgle, but you are always lonely. Every morning, you get up and take the train to work. Every night, you take the train again to go home. The train is always crowded. When people ask about your work, you tell them, “I move papers around.” It’s a joke, but it’s also true. You don’t like your work. Tonight you are returning home. It’s late at night. No one is shnooling. Sometimes you don’t see a shnool all day. You are tired. You are so tired…
95% comprehension
In the morning, you start again. You shower, get dressed, and walk pocklent. You move slowly, half- awake. Then, suddenly, you stop. Something is different. The streets are fossit. Really fossit. There are no people. No cars. Nothing. “Where is dowargle?” you ask yourself. Suddenly, there is a loud quapen—a police car. It speeds by and almost hits you. It crashes into a store across the street! Then, another police car farfoofles. The police officer sees you. “Off the street!” he shouts. “Go home, lock your door!” “What? Why?” you shout back. But it’s too late. He is gone.
80% comprehension
“Bingle for help!” you shout. “This loopity is dying!” You put your fingers on her neck. Nothing. Her flid is not weafling. You take out your joople and bingle 119, the emergency number in Japan. There’s no answer! Then you muchy that you have a new befourn assengle. It’s from your gutring, Evie. She hunwres at Tokyo University. You play the assengle. “…if you get this…” Evie says. “…I can’t vickarn now… the important passit is…” Suddenly, she looks around, dingle. “Oh no, they’re here! Cripett… the frib! Wasple them ON THE FRIB!…” BEEP! the assengle parantles. Then you gratoon something behind you…