I hope everyone has settled into the new year well? January seems to have been to a bit of organised chaos really, but the year has started strong and February looks to be even more fun.
Season 2 Blog 2 is here, and wow I’m excited for this one! This month’s topic is on data accessibility. Data accessibility is a topic I have a vested interest in continuously learning more about, one that I can recognise in myself isn’t as good as it should be.
With that in mind, I am delighted to have Tableau Ambassador Emily Kund join for this month to talk all things accessibility. I find Emily such an inspiring leader. You only have to follow her on social media to see the way she focuses on making informed decisions in a meaningful and accessible way. Only recently I found out Emily was behind the Tableau Fringe Festival celebrating data in the community through events. You can check out more here.
If you aren’t already, please follow Emily on her socials. She can be found on Twitter, Tableau, and her blog site.
CJ: Emily, thank you for joining! I’d love to hear a little more about your data journey so far? What is your primary focus whilst working at Red Hat?
E: Thanks CJ! I’m super excited to be here! I’ll try to hit the highlights here, but I’ve been working for like a gillion years, soo….
My journey started as a bank examiner using bank performance reports to see what was happening at banks and then using that data to inform my questions and conversations with bankers. From there, I was a business system administrator for a data retrieval tool (that’s where I learned that a space is a character!). Then I had the opportunity to lead a Reporting and Analytics team, which is where I really was able to start championing Tableau as a solution where it made sense. I wanted Tableau dashboards to be in the hands of the examiners we had spread across the country so they could turn insights into actions or have them ask the next best question. Two years after going to conference (2013), I started falling in love with data visualization. After my time in the public sector, I trained junior consultants and corporate on Tableau and data visualization. And now, I get to do all the stuff I wish I could have been paid for. I blog, I create training, and I get to help people create dashboards that facilitate data-informed decision making. Recently, I’ve been working a lot on our e-learning program we’re putting in place called Viz City (I am BEYOND excited for it!!)
CJ: In your past you’ve tended to do a lot of work in the realm of instructor courses, volunteering, training and being an advocate of others. It brings with it a real sense of community. Would you say giving back and helping others is something you’re hugely passionate about?
E: Yes!! Service is a big core value of mine. My dad was in the Lions Club when I was young, so I was always helping him with organizing paperwork (which wasn’t fun), but the one moment where I saw impact was when I went with my dad to visit the Leader Dog School for the Blind. At 15 years old, I got to see how the money raised by the Lions supported this school. That evidence of giving back has stuck with me.
CJ: At TC21 you hosted a session on inclusive design, focusing on transforming dashboards promoting engagement and accessibility. Thank you for sharing your personal and family story around data accessibility. You discuss your definition of accessibility vs Microsofts and the desire to design for as many people as possible. What do you consider the core fundamentals / the must haves in data visualisation design?
“This data accessibility journey isn’t just for others. It’s for me too.”
E: Oooh, this is a great question! I think you start with WCAG standards for accessibility and then by truly knowing your audience, you make adjustments from there. I think there are some things that are a given, chief among them, contrast.
Make sure everything in your visualization has a sufficient contrast ratio (WCAG provides specific guidance on this).
Blank space (also called white space) is your friend.
Use a legible typeface (be aware of mirroring and imposter letters). My favorite web-safe font is Verdana.
Don’t rely primarily on color.
There are a couple of other major points that WCAG talks about including keyboard navigation and being screen reader friendly (my words, not theirs).
Here’s why this is a challenge and a tricky question. Let’s say the perfect chart type for the data is a scatterplot that I can color encode (think clustering). On one hand, this is perfect because the audience can see the correlations in the data. But, the issue with a scatterplot is that the marks often overlap (which goes against the ‘ensure sufficient blank space’). What’s a dataviz developer to do? That’s why I think knowing your audience is so key. If I know my audience and I know they don’t have an issue with a simple scatterplot, I’m more inclined to use it because my audience will comprehend the message the data is conveying pretty quickly and easily.
That’s why I think this question is great. In my opinion, I think you have to start with accessibility and then adjust due to your audience (not you…unless you’re developing a viz for yourself).
Sometimes you have to unlearn what you learned. For me, the aha moment was double-encoding. I learned early on that you don’t need to double-encode. But for accessibility, double-encoding can actually be really helpful!
I feel like I’ve said too much for this question, but there’s so much to learn and do!
CJ: Do you think companies should focus on building out a styling guide framework and design toolkit to be consistent with conventions and promote accessibility within it?
E: Yes!!! I think it’s important to bake these guidelines in so that it
1) prioritizes accessibility from an organizational perspective and
2) helps people create more accessible data visualizations.
Having said that though, I think it’s also important to train people on accessibility, so that the person understands why they’re doing what they’re doing. It’s like the red/green color issue. On the surface, we know that red and green present a problem for a lot of people who have a color deficiency. However, there’s a strong color association (at least in America) with red and green (bad/good, less/more). So if you think about one of the chief items a data visualization should have (contrast), then you could in fact use red and green, as long as there is sufficient contrast (I’m a fan of light green/dark red).
CJ: You share tips on building with awareness to sight, dexterity and comprehension. One thing I particularly liked was the thought process behind reducing the number of clicks to get to insight. Do you have any examples of how and where this is particularly done well?
E: Crikey! There’s not one that comes to mind! And the reason why I struggle to give you a solid example is that it’s so situational. In some of the public data vizzes I see, it’s an exploration of a story, and I’m engaged so it doesn’t feel like there are unnecessary clicks. I know I sound like a broken record, but this is where knowing your audience definitely comes into play. And based on that, how quickly can I provide the necessary relevant information to get from point A to point B.
E: From where I sit, it’s still a focus on the basics. We have *got* to get those right. Eye tracking or object-based interactions on a page is great for knowing how your users interact with a viz, but we still have to get the basics right. I will fully admit that I focus on the basics more than the tech because I strongly believe you need to be informed about the topic, then you can make short-cuts (or efficiencies with tech).
CJ: You share a number of resources in the slide deck for the session, covering things such as colour pickers. Are there any other resources you’ve come across since that you’d like to call out?
E: Chartability! I mentioned it in my presentation, but I’ve used it and the color picker that’s mentioned in there for self-assessments/reviews of vizzes. Frank Elavsky has put a ton of work into it and it is such a good resource. In my opinion, everyone should take their visualizations through the POUR portion at least to see how accessible their data visualizations are.
CJ: Your presentation beautifully showcases ways as developers we can be more inclusive in terms of data accessibility and how we can apply it to the business setting. Do you have any tips on how we can improve accessibility through an organisation from a top-down approach too?
E: This is such a thoughtful question. I think it starts with how inclusive the culture is to begin with. One of the things I like about working at Red Hat is that they have communities built around inclusivity and accessibility. Having management support for this work is key! I am SUPER pumped for the Accessibility Day of Learning that’s coming up at work!! That recognition that we all have value and that our differences provide perspective permeates through the company. So now, making our work more accessible has buy-in from management. I am a big believer in culture starts at the top.
As for a tip, ‘squeeze the balloon at both ends’ approach. Meaning, I’d try to effect change at the management level with an accessibility analysis (the costs/benefits including legal) to show why we should consider accessibility in our work. Then, I’d also look for the people interested in doing the work and go from there. As I’m writing this, I almost take for granted something that I’ve been doing for awhile, but isn’t always available in organizations. And that is to share resources or blog about it internally. Give people resources they can use (this requires that management has set up the infrastructure to share this information).
CJ: Is there anyone in the data viz community that focuses particularly well on designing accessible dashboards? What do you particularly like about them?
E: This is actually a hard question because there are so many variables to it. I think accessibility is an emerging area of focus and in some cases you can’t just look at viz and say, “Oh yeah, that’s accessible” (because for one, you’d have to test it with a screen reader). Also, I’m not scouring Twitter or Tableau Public for accessible vizzes. Wouldn’t it be great if we used the #accessibleviz when we want to show off a viz that we’ve made that we believe is accessible? Having said all that, the most accessible dashboards are those that are clean, simple, and have contrast.
CJ: I often see you use the hashtag #a11y on social media. What does this term mean to you?
E: To me, it means that I advocate for accessibility. I may not get it right, but I try. And I’m interested in learning more so others can have a similar experience as me, because why is *my* experience more important than someone else’s?
CJ: Is there anyone you would like to call out that is a particularly good #a11y and actively promotes accessibility?
E: Frank Elavsky, Chris DeMartini, Amanda Makulec, and Amy Cesal are the first folks that come to mind. All of them champion and provide resources for accessibility.
CJ: Within the community sometimes there are some artistically creative designs that may not conform to what individuals typically see in the remit of data visualisation, where the work tends to lean more towards abstract graphic illustration compared to traditional data visualisation. Do you think this has come at a trade off for accessibility, and how can we ensure visualisations accommodate both design abstraction, readability and storytelling?
E: My short answer is yes. On one hand, I would say that something has to give and it’s a matter of what and how much. I think there are some things that can be done regardless though, like using high contrast or a good font, and alt-texting images. When I think accessibility, I think simplicity. I also think that perhaps there’s a bit of a mindset shift for some; simple can be beautiful. Additionally, knowing your audience will help with the readability. Sometimes I see visualizations and I think: I have no idea where to start or how I’m supposed to engage. That little bit of direction (through text in the visualization), can be helpful and help guide the data experience. I think it would be amazing for someone who loves the abstract to create a visualization and then take steps to make it more accessible and see how the final results comes out. That would be a fantastic challenge!!
CJ: With this in mind, could you share some tips to help companies improve their division on accessibility that go beyond data visualisation builds? I particularly like one you re-shared on Linkedin around Zoom and live transcription. How does having a good company culture impact fears of stigma around invisible disabilities?
E: Company culture is EVERYTHING! I felt supported and psychologically safe to make a public post about my depression and Fibromyalgia. It’s about having employee resource/network/working groups for diversity of people, including invisible illnesses. I think there are examples of cases where there was a cost of not having a product be accessible (Domino’s is one example). I think there are simple things which also correspond to data visualization tips:
Don’t use Arial in your Google docs. I know it’s the default typeface. Verdana is a good alternative.
Slide decks need to have a good color contrast and space to breathe. Don’t give people a novel on your slides.
Provide your slide deck to your audience. This allows audience members to zoom, read, and/or comprehend on their own, instead of relying on the presenter.
Close caption your videos, not just during Zoom meetings. If you’re posting up tutorials, order a transcription. We have a service we use at Red Hat, but YouTube has this ability. You can even order transcripts at low cost from Scribie.
There are so many aspects to creating inclusive products, so this doesn’t cover everything but it will definitely help take the first few steps towards an inclusive culture.
CJ: You host the vizzies each year during the Tableau conference to celebrate some memorable achievements of the Tableau community. Can you tell us how and why the vizzies originate? Are there any specific award topics that are special to you?
E: The Vizzies started because we wanted to celebrate the members of the community who were not Tableau Zen Masters because there were (and are) a lot of people doing a lot of great work. I’ll never forget gathering in a hallway and shouting out the awards! People who didn’t follow us on Twitter or listen to the podcast thought we were crazy. It’s crazy to me to see how we’ve grown and that we’ve been a part of the conference schedule and on a live (and virtual) stage. And I love seeing this little thing we started, which now people put on their social media profiles; it’s amazing! I think the award that is most special to me is the Michael W. Cristiani Community Leadership Award. A lot of people didn’t know Michael, who passed away in 2018, but they have definitely felt the ripple of his impact. Michael was a quiet leader who always looked to connect and support people. I’ll never forget going through some really rough times and Michael sending me messages of support. When Michael passed, Matt (Francis) and I felt compelled to rename the award after him because this is our way of keeping new community members aware of Mike’s impact.
CJ: As part of wanting to improve I have a bit of a strange question! If I was to ask you to pick one of my dashboards on my profile and asked for feedback in terms of some key components around building for sight, comprehension and dexterity what would you consider amending?
CJ Note: Please note I’ve specifically asked Emily for this feedback and wouldn’t advise doing this in the wider community without the permission of the person first as it may not come across as intended.
E: I chose to look at your Cristiano Ronaldo viz. First, I love the design of it, it’s so clean!! I’ll just write a few observations on the areas where you could make it more accessible. One of the biggest issues is that the background image does not have alt-text. Considering that you are conveying information in the background, there should be text that repeats the text you’ve included in the image. Since that might get a little tricky with such a large background image, I’d explore having a few images for each section that you’d want the reader to read (in this case, your color blocks might be a great way to section the images).
The typeface for Cristiano in the shield is hard to read, but that’s something that I think isn’t a showstopper (because we know the viz is about Cristiano Ronaldo and we can read the word Ronaldo.
The Shot Map is a bit problematic for two reasons; 1) you’re relying solely on color to convey information. Screen readers can’t read color. I totally get why you used this scatterplot map because it’s meant to look like part of the field with soccer balls/footballs. Double encoding would be my first piece of advice to make it more accessible, but at the end of the day, it may depend on your audience (if they aren’t using a screen reader, then what you have looks pretty good). The second issue is that the marks are overlapping. This is just an issue with this type of graph. WCAG guidelines recommends 1px white space (aka blank space) between data elements).
Another major issue I found is the data window. And this is most likely problematic for many infographic/highly stylized data visualizations or data art. This is what a screen reader would read.
All of those calcs to make the viz work will be read by a screen reader. That doesn’t seem like a good experience to me.
Finally, and this is another reason why alt-text is so important for this (type of) visualization. Because you have a novel/unconventional chart (the polygons), even though you’ve explained how to read it for sighted readers, the screen reader can’t read it without alt-text, so it makes it even more challenging to read.
I didn’t do a full review but those are the things that stand out to me.
CJ: Thanks for that. I am hoping in future visualisations you see a real change in how I build my experimental public work. I see from your site you have a vested interest in entrepreneurship as well as blogging and podcasting. What a plethora and range of skills. What’s coming up in 2022 that you’re particularly excited for?
E: From a dataviz perspective, I’m excited to learn more about human-computer interaction, UX, and accessibility. From a life perspective, I’m looking forward to walking in a New York Fashion Week event later this month, competing in a few pageants…such as the All American Pageant system), and hopefully getting into Quantic School of Business and Technology for my Executive MBA and hopefully passing the two courses I’m taking this year for my Micromasters in Analytics from Georgia Tech/EdX. I’m looking forward to earning my red belt in Tang Soo Do, and being happy and healthy.
I really admire Emily not just for her knowledge and skill set but her ability to open up conversations on social media that used to either not happen or be shied away from, especially in respect to health, well-being, accessibility and invisible disabilities. It really pays testament to her honesty and openness, it is very refreshing to see.
I’d like to see the hashtag of #accessibleviz to come alive.
I recently had the pleasure of sharing feedback to some IronViz entrants, and really admired some of the thoughtful commentary Emily gave around accessible design tips. Major thanks goes to Sarah Bartlett for organising these sessions, the effort she put in behind the scenes made for what was quite the flawless structure covering all timezones.
Good luck with the micro masters Emily, and thanks for joining!