Even better, they tweeted it!
…The diagram which is to affect thro’ the Eyes what we fail to convey to the public through their word-proof ears.— Florence Nightingale
Seriously, I’ve made many blogs and posts over the years. The demise of old social networks, hackers, and just plain time have ended the usefulness of many of these.
My hope is to make aeoneal.com a place to gather the best of the old and whatever is new under one roof. If you see blogs you previously read on UXtraordinary, aleXfiles, LiveJournal, cognitions.net (no longer mine), offmostcharts, Medium, or anywhere else online, that’s why. Dates are from original posting, or occasionally from the time of an event. Dates after this post are as they happen.
Cross-posted from my Medium blog.
Everyone uses them: Green, yellow (or orange), and red. We use them in data visualization, we use them in buttons, we color text and icons with them and put them into alerts. They are often used in crucial moments, when we are announcing success, or breaking bad news. We abuse them, too, using them to draw attention where they aren’t relevant. What we don’t do, far too often, is make them accessible.
A significant minority of people are color blind, and most of those have red-green color blindness. Since 2011 I’ve had to solve for color accessibility in important interactions, such as alerts for patient vitals, quality of patient care, cloud server status, or executive sales analytics. Here are some accessibility tips I’ve picked up along the way, as well as my personal template for a usable, accessible traffic color palette.
Use icons as well as color
You may design a beautiful, color blind-friendly palette, but it never hurts to reinforce the message. Instead of changing text to red or green, put a differently shaped red or green icon next to the text. That way, even if you have no control over your color palette, or the chart has been printed in black and white, or your user sees only in grays, you’ve made your point.
Case in point: Excel. Excel offers icons in traffic light colors to help tell your data story. Make sure you use differently shaped icons as well as different colors! Here’s why:
Deuteranopia and protanopia are two common types of red-green color blindness. Testing your colors against them will optimize for most of your users, but icons help seal the deal.
Don’t trust preset color palettes
There are many extremely useful frameworks and boilerplates online. Each meets many needs, but not all have had the time to optimize their colors for color blindness.
The most important question when looking at your reds, greens, oranges, and yellows is, “Will my users recognize this color when they see it by itself?” Don’t trust the people who created your framework to have thought of this. Check it out for yourself.
Common colorblindness checking with Adobe
How do you do that, you ask? For many years the only solution I found for testing was Adobe’s PhotoShop, which offered protanopia and deuteranopia views of whatever I was creating. The options are under View → Proof Setup (see image below).
Recommended online colorblindness checker
The Corblindor Coblis (Color Blind Simulator) is now my go-to tool. Just do a quick screen shot of your work, and see how it looks for many different types of colorblindness.
Plan ahead with a color template
I’ve done a lot of data visualization color work over the years, and a pattern has emerged that I find helpful. I’m offering it here, in the interests of making data more usable. I strongly recommend considering this approach when you’re developing a brand color palette.
Here are the key guidelines:
- Use a light, medium, and dark shade. Your yellow should be your light shade.
- Use a warm green and a cool red, or a cool green and a warm red. Just don’t have both cool or both warm.
- No orange. Because it’s so much lighter, using yellow instead of orange makes it much less likely your “warning” color will conflict with your “success” green to color blind users, or look too much like your “serious problem” (errors, e.g.) red.
That’s it! Thanks for reading. Go forth and have fun telling good stories with your data.
One’s destination is never a place but rather a new way of looking at things.— Henry Miller
I was thrilled to be able to share my design-focused narrative taxonomy concept and process at the Austin UXPA, hosted by Rackspace. Great crowd, great discussion, great experience. Thanks to organizer (and user research guru) Candice McFarland for organizing this!
Originally posted on former personal blog UXtraordinary.com.
Cross-posted and expanded from my LinkedIn account.
Everyone demonstrates the fundamental attribution error—a variation of correspondence bias (pdf)—to some extent. We look at the action and assume it’s the character. Even when we know there are extenuating circumstances we do it. The defense lawyer, doing his duty to provide the best defense possible, is seen as supporting crime. The debate student, assigned to defend a certain position, is seen as believing it; no matter the usefulness of the role or the purity of intent, every devil’s advocate runs the risk of being seen as devilish. And of course, the criminally negligent incompetent person driving the car that just cut us off.
In the workplace this can create misunderstandings, usually small but sometimes project-killing or even career-destroying. It’s a problem because the only way to overcome correspondence bias and not commit the fundamental attribution error is to constantly question your assumptions and opinions, looking for the larger context.
Since we’re all story-driven creatures, sometimes an anecdote can help. This is a story of a time a life was on the line, and it’s the best example of correspondence bias I know.
My mother’s uncle was a man named Jara. He was my grandmother’s brother, an artist when he could be (I saw beautiful sculptures and drawings in his widow’s home). His best friend, whose name I don’t know, was a professional artist.
During Hitler’s occupation of Prague, Jara and his best friend were sent to a labor camp. At the camp worked another man whose name I don’t know. Let’s call him Karel. Karel worked as an overseer, managing his fellow citizens for the Nazis. Karel was hated. He treated everyone “like a dog,” Jara said, swearing at them and driving them mercilessly, generally making the labor camp experience every bit as awful as you imagine it to be.
Watching Karel’s behavior, day in, day out, Jara and his friend eventually realized Karel could not be allowed to live. It was obvious to them. Karel was a traitor, a collaborator with the enemy, and responsible for much misery. They were young, and passionate about their country. They made a pact together, that if all three of them survived the war, Jara and his friend would hunt down Karel and kill him. They viewed it as an execution.
The war ended, the labor camp closed, and life continued for all three men. Jara and his friend discreetly found out where Karel lived. They obtained a gun, and one day they set out to his home.
Karel lived outside Prague, in a somewhat rural area. When Jara and his friend arrived, Karel’s wife was outside, hanging laundry. When they said they’d known Karel at the labor camp, she smiled and invited them in, calling to Karel that friends from the camp had arrived. They followed her to the kitchen, where they found the monster they sought.
Karel was sitting by the table with a large tub of water and baking soda in front of him, soaking his feet. He was wearing rolled-up pants, suspenders, and a collarless, button shirt, the kind you could put different collars with under a jacket. He greeted them with a broad smile, immediately calling them by name and introducing them to his wife. Jara said Karel was so happy, he had tears in his eyes. He asked his wife to give them coffee, and she brought out pastries, and all sat down to talk about old times.
Jara and his friend were dumbfounded, but did not show it. During the conversation they realized that Karel had not thought of himself as collaborating with the Nazis, but as mitigating their presence. He was stepping in so no one worse could. His harshness was protective; the Germans could not easily accuse the workers of under-producing when Karel pushed his fellow Czechs so hard.
They stayed several hours with Karel and his wife, reminiscing and privately realizing no one was getting shot that day, then took their leave. On the way back they threw the gun into a pond. Jara went on to work at the Barrandov film studios, where he met his wife, Alena (she was an accountant). They married, lived a long life, and were happy more often than not.
Jara was transformed by this experience. Never again would he take any person’s actions as the sum of their character. And I do my best to see things in context and not judge, in part because of the man my great-uncle didn’t kill.
Leadership is the big skill of getting groups of people to complete the right work.— Clark Aldrich
At SXSW I had the pleasure of sitting in on Andy Barr’s and Sarada Peri’s 37 Practical Tips to Help Your Write & Speak Better. Much of these focused on simplicity of grammar and content, and reminded me of the writer’s vow of chastity my husband conceived back in 2007. Since then, my first drafts attempt to follow the below rules as much as possible. Only then do I go back and add anything more, trying to restrain myself to choices that add clarity.
So here it is.
Just as Lars Von Trier and Thomas Vinterberg wrote the film maker’s vow of chastity (also know as Dogme 95), so Bart has proposed a writer’s vow of chastity.
A draft of the rules as of August 4, 2007:
The writer’s vow of chastity
The writer will use no modifiers.
- No adverbs.
- No adjectives.
The writer should act as a behaviorist.
- No words describing emotion.
- The writer will not make the reader directly privy to a character’s thoughts (no interior dialogue or interior monologue).
The writer may break these rules only when it is unavoidable.
The above may be summarized as, “Not doing the reader’s work for them*.”
*The summary references advice from C.S. Lewis to his students:
Don’t say it was “delightful;” make us say “delightful” when we’ve read the description. You see, all those words (horrifying, wonderful, hideous, exquisite) are only like saying to your readers “Please will you do the job for me.”
Barr and Peri also provided a page with the 37 tips, on which I took copious notes. Here it is—enjoy!
…Don’t say it was “delightful;” make us say “delightful” when we’ve read the description. You see, all those words (horrifying, wonderful, hideous, exquisite) are only like saying to your readers “Please will you do the job for me.”.— C.S. Lewis