A Call to Viz Responsibly
How we got here
When I studied public health, chart design was prescriptive: lines for trends, bars for categories, and chart titles that described the metric rather than the message. Health data deserves better, and the modern world demands more.
Over the past 15 years, I’ve worked with public health projects and organization around the world on building more effective data visualizations. Sometimes that’s data storytelling, sometimes that’s what dashboards.
In March 2020, as the COVID case datasets were sweeping the data viz world, I wrote an article for the Data Viz Society’s Nightingale journal titled “Ten Considerations Before You Create Another Chart about COVID-19.” Throughout the pandemic, it remained one of the most read articles on the site.
The case data was woefully incomplete at the time, with access to testing and lag times with reporting results varying wildly across countries, but also across state and counties here in the US. Everyone seemed keen to build their own tracker for the virus, often without acknowledging the many issues with the source data.
Throughout the pandemic, I wrote additional articles on how case data was collected and demystifying COVID data (Fast Company). I thought having a better understanding of the nuances in the data would help people make more informed decisions around how they used that data. Maybe they’d see how daily fluctuations in case counts shouldn’t have dramatically change decisions about adopting public health prevention measures, like social distancing, masking, and eventually opting into getting vaccinated.
Nuance doesn’t go viral on social media though. What often does are anecdotes and stories. I learned that lesson on a deep, personal level when two of my tweets went viral in the wrong way. One, about opting to be vaccinated while pregnant, and a second sharing about the death of our son, were repurposed as an anti-vaccine meme days after he died.
I’ve written about that experience (New York Times) and the pain it caused for our family. But what’s stuck with me, more than three years later, are the ways that personal stories are so much stickier than charts. No bar chart or risk ratios around the protective benefits of vaccination, or the risks COVID posed to pregnant woman, would be more eye catching and emotionally gut-wrenching as an anecdote about the death of a child. But individual anecdotes shouldn’t be all that informs big decisions: for those, we do need data.
Data visualizations make patterns in often massive tables of information instantly recognizable, by leveraging our ability to do preattentive processing. You see a line going up, you intuit that something increased; you quickly pick out the longest and shortest bars on a bar chart. But what if under that summary number is a distribution of different data points that tell a very different story? What if the title someone writes on the top isn’t quite right, but sticks in your mind with memorable alliteration?
In today’s world, images and information move quickly and are hard to erase as they move across the internet - I know well from experience as we tried to get the AV meme removed. That puts a greater burden on anyone creating or sharing information to consider our responsibilities to inform, not mislead.
About my work
I work with teams to design impactful data visualizations, from static charts and slide decks to reports and interactive dashboards that enable the story-finding necessary to enable data storytelling. I apply human-centered design and agile methods to data projects, and enable organizations to do the same.
I also lead workshops and speak about data visualization, with the goal to inspire others to dive into the data viz world.
That purpose has inspired my leadership of the global Data Viz Society, with the aim to nurture, celebrate, and advance the field of data visualization.
Across all of my professional work, I consider the impact and unintended consequences of the charts we share, particularly in our AI-enabled world where meaning and trust in data requires keeping a human in the design loop.
Throughout the pandemic, I occasionally wrote or spoke about the necessity of visualizing data responsibly around COVID-19. I focused on other projects, including client work, the Data Viz Society, and parenting with two young kids at home. I moved from DC to Wisconsin in the midst of the 2024 election cycle, and suddenly got to see what campaigns and attack ads look like in a swing state. As we close out 2024, I’m cringing as people who willfully peddle misinformation elevated to positions of power.
Which brought me back to this Substack page that I created back in 2020, but haven’t posted on since. It’s time to revisit the call from nearly five years ago to #vizresponsibly.
What you can expect from this newsletter
I’m not a big fan of gatekeeping knowledge about data visualization. I believe that anyone can (and should) become a more informed reader or creator of charts; sometimes more chart-reading sends you down the path to some chart-crafting too.
My goal with this newsletter is for anyone curious about data communication build those skills, with a focus on the nuances of visualization.
I’ll unpack charts making deliberate design decisions to communicate information clearly, and explore why other charts fail. I’ll dig into some of the ethics and challenges for crafting and consuming data visualizations in an world where gen AI capabilities to spin up a quick chart grow each month (though they’re still falling flat if you ask many of us who work in this domain). I’ll highlight insights from papers from the data viz research world. And I’ll give you actionable tips for ways you can build your own data viz skills to visualize data responsibly.
Many of the charts I dig into focus on science communication, public health, and advocacy, though what’s top of mind each week may also be shaped by current events or personal conversations. Variety keeps things interesting!
Today, more than ever, we need everyone to build their skills to spot misleading charts and graphs, intentional or not. Spend 10 minutes with this newsletter each week, and I promise you’ll build your own abilities to #vizresponsibly whether you consider yourself a data viz expert or just data curious.
