Accessibility means different things to different people.

I see two main types: Big A and little a.

1. Big A Accessibility means that our graphs meet official accessibility guidelines so that they’re understandable for people with disabilities. In the United States, that means 508 Compliance.
2. Little a accessibility means that our graphs are understandable for non-technical audiences; skimmable; and generally not a garbage heap of jargon.

Both Big A and little a are central in my work.

Here’s where you can learn more.

Big A Accessibility

Here’s a (partial) list of everything you’d need to do to pass 508 compliance guidelines.

Directly Label

Remove legends and directly label the data.

Add White Outlines

Outline the touching, filled shapes with white borders (i.e., cells in a heat map, slices in a pie chart, locations in maps, rectangles in stacked bar charts).

Make Sure Graphs are Legible for People with Color Vision Deficiencies

Red-green colorblindness isn’t the only type, but it’s most common.

And, it’s the most problematic for data visualization. We love to use “stoplight coding,” especially in dashboards. We’ve all seen dashboards where green means “we met the target” and red means “we didn’t.”

For people with color vision deficiencies, those reds and greens just look like yellows all blended together.

Tips:

• Avoid red-green color combos (try red-blue, orange-green, or orange-blue for stoplight coding instead).
• Use direct labels.
• Test your drafts.

Make Sure Graphs are Grayscale-Friendly

Printing is less common nowadays, especially with so many people working from home indefinitely. Who wants to pay for their own color ink?!

Your infographics, reports, slideshows, and reports might still be printed.

And they might be printed in grayscale.

Let’s plan for grayscale printing ahead of time to make sure the visuals will still be legible, just in case they’re printed.

Tips:

• Use direct labels.
• Add white outlines.
• Test your draft.

Use Plenty of Color Contrast

The other night, as I was reading my 4-year-old a bedtime story, I was struggling to read the words on the page. The book used colored font against a colored background, and the words were kinda small. Those were all fixable problems!

Tips:

• Don’t use colored text against a colored background. Here’s how to place text on top of photos so that it’s legible.
• Make sure all your colored text (e.g., for headings) is bold.
• Make sure your grays are dark enough. Software defaults are terrible at this. Enlarge and darken those defaults!!

Use Larger Fonts

Increase the font size (I recommend 11+ for documents and 18+ for slideshows, not Excel and Tableau’s puny size 9 defaults).

Again, the software defaults don’t help us here. Their defaults are usually way too small.

Add Alt Text

Add alt text to all images for standalone documents (reports, dashboards, infographics, etc.), including graphs.

Molly Burke’s Instagram is my favorite alt text inspo.

little a accessibility

These are techniques that won’t necessarily help you pass official accessibility guidelines… but are still a good idea if you want to make charts that people actually understand and use.

Actually Use Graphs

Use less text and more graphs!!!

Add graphs alongside those boring bullet points.

Choose the Right Chart

Go beyond the bar chart.

Use Data Storytelling

Use data storytelling, which I define as:

• writing takeaway titles instead of topical titles and
• highlighting one key finding at a time in a darker color.

Color-Code by Category

One of my favorite techniques of all time.

Color-coding by category helps us chunks the information into manageable pieces.

We can color-code in presentations, reports, dashboards, and one-pagers.

Lower the Reading Level

I’ve written about reading levels several times:

• In this blog post, you’ll see a re-written chart title for a conference slide.
• Here are some common data phrases, re-written.
• Here are some common research methods phrases, re-written.

Lower the Numeracy Level

Here’s how.

Use a Consistency Text Hierarchy

Make sure all the Heading 1s match, all the Headings 2s match, and so on.

Use Horizontal Text

It’s faster to read than diagonal and vertical text.

Avoid Underlines

Only use underlines for hyperlinks (not for headings).

Avoid ALL CAPS

It feels like shouting and takes longer to read than mixed case letters.

Place Text Next to the Graph

Not on the next page so that it’s faster to read.

Add Symbols and Icons

They make graphs easier to navigate and they boost the memorability of our findings.

• Here’s an example with state icons.
• Here’s how to use the StateFace font.
• Here’s an example with realistic human icons (instead of gingerbread people).
• And the realistic human icons, in a GIF!

Presentation-Specific Techniques

Talk about one thing at a time so that what your audience is hearing and seeing match.

Use a microphone!!! In-person and online. I don’t care if you think your voice can fill the room. It can’t, especially for people who are hearing-impaired. For virtual presentations, purchase a microphone. Or, at the bare minimum, wear the earbuds that came with your phone (because they likely have a built-in microphone). Tinny, echo-y sounds are hard for all of us.

Report-Specific Techniques

Follow the 30-3-1 approach. Limit the body to 30 pages (or less!), and then create a separate 3-pager and 1-pager.

Use visual appendices instead of black and white appendices to make the patterns more obvious.

Dashboard-Specific Techniques

Don’t expect busy, non-technical audiences to interact with your dashboards.

Involve the End Users

Involve the end users in the sensemaking process, e.g., by using data placemats and by following the Choose Your Own Adventure method in presentations.

Listen to what users say they need… but give them what they actually need.

Remember the Humans Behind the Data

I love this example.

Your Turn

Which of these techniques are you already using?

Why techniques might you try in the future?

The post “Big A Accessibility” and “little a accessibility” Tips for Data Visualization appeared first on Depict Data Studio.

I did.

I taught myself how to write in third-person language.

I called myself “The researcher…” instead of plain ol’ “I…”

I replaced my everyday words with “smart” synonyms. I literally paged through my GRE study guide. I tried to use as many GRE vocab words as possible.

Then, I started working in the real world.

My bosses rolled their eyes.

Another one from an academic background, they sighed. We’ll have to re-train her from scratch.

I panicked. But if I wasn’t supposed to sound like a textbook, what was I supposed to sound like???

A human!

It took me years to grasp that simple concept. I’m a person. It’s okay to sound like a person.

Nowadays, I make a living by teaching humans how to sound like humans again.

Before/After Makeovers for Common Methodology Sentences

Here are some before/after examples in case you’re still on the textbook-back-to-human journey like I was.

Please please please use these transformations in your technical reports.

I’m not so worried about peer-reviewed journal articles — that’s another battle for another day. Today, I’m focusing on your non-journal writing scenarios.

Who Designed the Survey?

• Before: A survey instrument was designed by the ABC Research Company working under the supervision of the DEF Foundation staff, and key department heads of GHI Agencies.
• After: The ABC Research Company, DEF Foundation, and GHI Agency teamed up to collect data.

Who Responded to the Survey?

• Before: A series of survey instruments were developed to administer among students in the ABC programs.
• After: We designed surveys to collect information from students in the ABC programs.

How Many Responses?

• Before: A total of 14 programs participated in the survey.
• After: Fourteen programs participated in the survey. (Remove redundancies like “a total of.”)

Or…

• Before: A total of 144 programs participated in the survey.
• After: We collected surveys from 144 programs. (Because writing out numbers at the beginning of a sentence is the worst.)

When Did You Collect Data?

• Before: Initial surveys were launched on March 7, 2018 with fieldwork continuing to accommodate the schedules of participating institutions. Data collection was cut off on April 25 to begin data processing. A total of 789 surveys were attempted, with a total of 654 surveys completed sufficiently to include in the final tabulated results. A total of 123 individuals entered their contact information for a drawing.
• After: We collected surveys in Spring 2018. We tried to collect data from 789 people, and 654 people participated, for a response rate of 83 percent—one of the highest response rates we’ve ever had on a survey.

Referencing the Just-in-Case Tables

• Before: We are providing detailed data tables with this report that shows the responses by institution.
• After: Want to view responses by institution? View the appendix on page 31.

Demographics on Respondents

• Before: Overall, undergraduate students comprise 65% of total responses and graduate students comprise the remaining 35%.
• After: Two out of three responses (65%) were from undergraduate students. The rest were from graduate students. (Getting rid of the word “comprise.)

Describing the Survey’s Topics

• Before: One way the important resources and individuals specifically helped at least two-thirds of students were giving them a good sense for the kinds of careers they could pursue with a degree.
• After: We asked students which resources were most useful. Two out of three students said that others had given them a sense of career options that they could pursue with their degree.

Summarizing the Survey’s Findings

• Before: The largest mean share of the total cost are paid for by the student or their family, who account for 50% of the total cost. Student loans are used to cover a mean of 20% of the total cost, and scholarships or other financial aid pay for 30%.
• After: For the typical student, 50% of their costs are covered by the student and their family, 30% are covered by scholarships or financial aid, and 20% are covered by student loans. (Getting rid of awkward language like “mean share” and “account for.”)

Objectively Scoring the Before/After Translations

In my gut, I know the translations are easier to read.

Let’s objectively test them.

Before: 12.1 Grade Level

The human-trying-to-sound-like-a-textbook wrote at a 12.1 grade level.

Okay, that’s not the worst I’ve seen.

The highest I’ve seen is a 36 (from a team of Ph.D. psychologists).

Can you beat a 36??? Let me know if you find any contenders. I’d love to (try to) read it.

(This screenshot is from Readable.com, which used to be a free reading level checker. It looks like they require payments nowadays, but there are plenty of free- and low-cost tools. Like good ol’ Microsoft Word! Comment below if you’ve got a favorite.)

A­fter: 9.3 Grade Level

I personally aim for grade level 6 to 8—throughout my blog posts, books, and even contracts.

I didn’t quite reach my goal. But a 9.3 isn’t horrible, either. The Readable site gives this an “A!”

Higher is not better. Lower is better.

You are a human who’s writing for humans. You are not a textbook. You are not a textbook. You are not a textbook. You are not a textbook.

How to Lower the Reading Grade Level

Try one (or more!) of these techniques:

• Shorten the sentences. An easy fix is to look at your longest sentences. Replace your commas with periods (i.e., break one long sentence into two shorter sentences).
• Shorten the paragraphs. Press the “enter” key lots and lots and lots.
• Use first-person language. Adjust the sentence structure. Change “A survey was administered…” to “The agency administered a survey” or “We administered a survey.”
• Find synonyms. This is the hardest one for me. What’s an accurate, understandable translation of calculations like standard deviation or confidence interval??? I used to pack those terms into the report’s body and hope for the best. What happened? Lots of Dusty Shelf Reports! Nowadays, I follow the 30-3-1 Approach to Reporting. I keep the methods section in the report’s body as short as possible, and I tell readers to check the appendix for more info. I don’t care if the appendix is packed with jargon. Only the technical readers are going to look there anyway, and they’ll understand the jargon.

Your Turn

Upload one of your own paragraphs into your favorite reading level checker.

How did you score?

And more importantly, how can you adjust the language to lower the reading level??

The post How to Write about Research Methods Like a Human (and Not a Textbook) appeared first on Depict Data Studio.

There’s a misconception that accessibility takes all day, that’s it’s costly, or that it’s complicated. Those are all false.

Accessibility is woven into all my trainings, but since this is a topic I get asked about a lot, I decided to make a new talk that’s focused just on accessibility for dataviz.

In Spring 2021 I gave a talk at the Good Tech Fest conference about dataviz accessibility quick wins.

The talk was “Choose Your Own Adventure” style where the audience chose what we discussed from a list of options. They chose:

• direct labels,
• lower the reading level, and
• lower the numeracy level.

You can watch the recording or read the highlights. Enjoy!

—–

Watch the Conversation

Why Bother Lowering the Reading Level?!

We’re writing for busy people. The ones who see tons of graphs coming into their inbox every day.

We need to lower the reading level.

Not because our readers are dumb, but because they’re busy.

They need to be able to understand what you wrote the first time—not the second, third, or fourth read-through.

Before: A Dense Slide Title

Here is a real-life graph from a public health agency.

I had to read this slide title at least five times to figure out what it was talking about.

After: A Skimmable Slide Title

I talked with the epidemiologist who made that slide, and here’s what we came up with:

Here’s what we did:

• We put the main takeaway point in the title.
• We used a text hierarchy so that your eye is drawn to the largest, darkest, boldest text first. 
• We kept her original title so that the technical people had all of the information they would need, but made it the subtitle instead.
• We rotated the diagonal text and used horizontal text instead (for speed-reading).

Objectively Testing the Reading Level

We tested both titles with an official readability website.

In the past, I’ve used https://readable.com/.

They used to be free, but now have a fee.

(Comment below if you have a great, free readability website you use. You can also use Word or Google for this.)

The before graph title was a 14.2, which in the U.S. would mean you’ve graduated high school.

The after version was a 6, woohoo!

The Average American Reading Level

Speaking of grade 6 being a great spot to be at.. What do you think is the average reading level?

Hint: it’s lower than you think.

The average American reading level is a 6 – 8.

While a lot of people have gone on to higher education levels than that, it’s not a one-to-one comparison.

For example, it’s not, “I finished 12th grade, therefore I read at a grade 12 level.” A lot of us read a little bit below our formal education years.

Rule of Thumb: Write 1-2 Levels Below

Sure, you might not be writing for “the general public.”

You might be writing for grant makers, policy makers, trustees, etc.—folks who likely read much higher than a grade 6-8.

A good rule of thumb is to aim for 1-2 levels below your audience’s education level.

For example, if I’m working on a board packet, and I know all the board members have an undergraduate degree, then I write two levels below that—at a middle school level.

If I’m working on a technical report for a government agency, and I know that all the recipients have Master’s degrees or higher, then I write two levels below that—at a high school level.

How to Lower the Reading Level

Here are some quick wins:

• Active voice (instead of passive voice)
• Shorter words, sentences and paragraphs
• Replace jargon with synonyms

After drafting your sentence or paragraph (they’ll probably be really long—mine usually are!), you’re going to go back and edit your writing.

Anytime you see a comma, replace it with a period.

Or, if your paragraph is six sentences long, break it into two shorter paragraphs.

Please make sure to objectively test your own writing (with Readable, Word, etc.). I don’t care what tool you use.

Let’s Practice

During the Good Tech Fest conference session, we practiced lowering the reading level for a few common data sentences.

How would you lower the reading level for these examples?

Example A: A survey instrument was designed by the ABC Research Organization.

The quickest wins would be:

• shorter words, sentences and paragraphs; and
• replacing jargon with synonyms.

Here’s the after:

What if you’re trying to explain the number of participants in a survey?

How would you lower the reading level here?

Example B: A total of 14 people participated in the survey.

Example C: A total of 144 people participated in the survey.

Here’s the after versions:

One last example with some jargon.

Example D: Undergraduate students comprise 65% of total responses.

How would you replace the jargon with synonyms to lower the reading level?

Here’s the after:

Your Turn

How’s the reading level in your writing? Comment and let me how your writing scored.

This blog post has a Flesch-Kincaid Grade Level of 6.3.

Download the eBook

Want to learn more about accessible data visualization?

In this ebook, you’ll learn 10 quick wins for designing accessible data visualizations. These small edits can have a big impact for our coworkers, board members, and funders who have color vision deficiencies, hearing loss, or learning disabilities–and for all of us who are pressed for time.

For your complimentary copy, use code: goodtechfest

The post Accessibility Quick Wins: Lower the Reading Level appeared first on Depict Data Studio.

• the graph type you select (3D exploding pie charts with 999 slices are inherently hard to read);
• font size (I suggest a minimum of 11-point font in reports and 18-point font on slides);
• text direction (we read horizontal text faster than diagonal or vertical text);
• colorblindness considerations (no red/green combos);
• grayscale printing considerations (test it beforehand); and
• the reading level of your titles, subtitles, and annotations.

Last time, I showed you this makeover:

In that before/after transformation, our goal was to make the years along the horizontal x-axis legible. Before, the labels were too small (size 9) and they were diagonal (which is slower to read than plain old horizontal text). We freed up space by abbreviating the years (1985 to ’85). We also opted to label just four points along the line to emphasize key milestones.

We also re-wrote the slide’s title. For slides, I aim for short titles (a couple key words). When the presenter is physically present, the presenter’s voice can elaborate on the cool parts of the graph.

The fewer words, the better. You don’t want to lose your audience’s attention, i.e., you don’t want them to be reading full sentences on your slides while you’re speaking. For other types of materials (like reports, handouts, and infographics), I use storytelling titles. Storytelling titles might be 6 to 12 words long. Storytelling titles give you room to elaborate on the cool parts of the graph, like the takeaway finding or “so what?”

Measure Your Text’s Reading Grade Level

While redesigning this graph, it took me a while to understand the slide’s title. There were a lot of technical terms that I wasn’t familiar with. I was also concerned about the title’s length.
I wanted to test my gut instinct. There are several free and low-cost tools for objectively measuring text readability.

I’ve used https://readable.io/ for years and love it. You’ll need to enter your email address. Then, you can access the free portion of the tool. You get 15 minutes of free usage each day. Or, you can pay $4/month for the pro version. I don’t get paid to promote Readable, but I probably should! I love sharing this tool with others.

I pasted the before title into Readable’s website: “Stage 3 (AIDS) Classifications and Deaths of Persons with Diagnosed HIV Infection Ever Classified as Stage 3 (AIDS), among Adults and Adolescents, 1985-2014 US and 6 Dependent Areas.”

The before title scored a D, yikes! The before title was a 14.2 grade level, which is equivalent to a high school diploma and two years of college.

Yes, this graph was designed for people who had college degrees. Just because your viewers can read at a 14.2 grade level doesn’t mean they want to read at a 14.2 grade level. Reading at or above your level would feel like homework. Do you want your graph to feel like homework??

(P.S. Readable’s website got a makeover since I wrote this blog post, so your view will look a little different.)

Measure Your Text’s Reading and Speaking Times

Readable also measures reading and speaking times. Our title took 6 seconds to read and 11 seconds to speak! The epidemiologist could lose her audience for an entire 6 seconds.

On another recent project, I measured a company’s entire draft report with Readable’s website. The report was around 100 pages long, and Readable told us it would take someone 16 hours to read! The report was designed for state-level policymakers. Are we really expecting a busy policymaker to set aside two full working days to read a report? We’re all inundated with information.

Cut down your document’s length by focusing on essential content. Push non-essentials to an appendix. Then, make the remaining text faster and easier to read.

Edit Your Writing and Try Again

I read the title again. And again. And again. And I finally realized that it was just talking about AIDS diagnoses and deaths.

I tried that new title—AIDS Diagnoses and Deaths. It scored an average grade level of 6.5. Hooray!

The average American adult has an 8^th grade reading level. This isn’t the time to laugh at people with 8^th grade reading levels. I could talk about the systemic problems with our educational system for hours.

Your audience may not be the general public, of course. Your audience might be your boss, or your Board of Directors, or state-level policymakers. Their reading levels may be much higher. Your audience doesn’t want to read at their peak ability for hours. Don’t make your graph feel like homework!

This shortened title will only take the audience a second to read—six times faster than the original.

Still Not Convinced? Here’s When It’s Time to Care About Reading Levels…

Look for these clues from your readers:

“Well.. I can tell that really smart people worked on this project.” The first few times I heard this feedback, I mistook it for a compliment. I thought, “YES!!!! I used all the terms from my grad school stats classes correctly!” Now, if I hear that feedback, I cringe. This “compliment” is a sign that your documents are too technical. It’s time to revamp your graphs and your writing style.

“The report was really… comprehensive.” Ouch! This “praise” is a sign that your documents are too dense.

“Thanks for sending the report to us. We’ll let you know if we have any questions.” Ouch! This “engagement” is a sign that readers aren’t connecting with your documents.

Lowering your document’s reading grade level won’t solve all your reporting problems, but it’s a first step.

7 Practical Tips for Improving Your Text’s Reading Level

Sold??? Ready to improve your readability???

I love Readable because it gives you practical suggestions for improving your writing. For example, in our before title, the website highlighted the word classifications in a darker color. It also told me I was using too many long words and that the sentence was too long.

Here are practical tips for lowering your text’s reading level:

1. Find synonyms for technical terms. In this project, we changed classifications to diagnoses. In another project, we changed the counterfactual to comparison group and described the nitty gritty details of the counterfactual analyses in the appendix. In another project, we changed at baseline to when people enrolled in the program.
2. Avoid acronyms. I don’t care if you define the acronym the first time you use it. I shouldn’t have to flip back to page 1 while I’m trying to understand page 10. I shouldn’t have to memorize acronyms in addition to understanding your content and visualizations. When in doubt, spell it out.
3. Use shorter words. Look for words with lots of letters and lots of synonyms, and then find replacements.
4. Write shorter sentences. One of my personal weaknesses is writing run-on sentences. As I edit my own writing, I break long sentences into several short sentences. Search for your commas and semi-colons. Replace them with periods.
5. Write shorter paragraphs. Several short paragraphs > one long paragraph.
6. Write narrower paragraphs. I was That Nerd who took a speed-reading course during high school. I learned about how our eyes scan a page from left to right to read a line of text. I was surprised to learn that we don’t actually look alllllll the way to the left or allllll the way to the right. Instead, our eyes stay towards the center and we take advantage of our peripheral vision to scan the words on the far left and far right. Accordingly, there are studies about how long we should make each line of text (i.e., how wide or narrow our paragraphs should be). Results are somewhat mixed; readers have personal preferences about exactly how many inches wide they prefer. Nobody can speed-read a super long line of text, though. In portrait layouts, I use one or two columns of text. In landscape layouts, I use two or three columns of text.
7. Remove redundancies. Say what you need to say—once! Avoid repetition across your sentences, graphs, and tables. I’ve got an upcoming before/after makeover blog post where I’ll show you how to remove redundancies.

I also have a personal preference for active voice and first-person writing. I can’t connect with reports that sound like they were written by robots.

Lowering your graph’s reading level is not the same as dumbing-down your graph. Lowering your graph’s reading level shows that you respect your audience. You recognize that these are busy, important people. Busy, important people have lots of busy, important priorities. Your graph is one of many, many pieces of information to come across their desk each day. Give your audience the information they want in a format that doesn’t take all day to decipher. Then, your audience can make informed decisions and move on.

Have you used other readability tools? Share them here!

The post How to Objectively Measure Text Readability (and Lower Your Graph’s Reading Level) appeared first on Depict Data Studio.