By Michela Tjan

I’m excited to be writing again for the Open Visualization Academy newsletter, and I wanted to share some reflections on a topic that’s been on my mind: the human side of data visualization.

When we talk about data visualization, it’s easy to think of it as just charts, graphs, and dashboards; tools to make numbers easier to digest. But reading about Professor Arvind Satyanarayan’s work at MIT reminded me that visualization is so much more than that. It’s not only deeply technical; it’s also human. It draws from psychology, cognitive science, design, and social responsibility.

His research shows that visualization isn’t just about presenting information, it’s about giving people the power to engage with it on their own terms. That idea of agency is something I’ve been thinking a lot about lately. In my own work, I’ve seen how empowering people to explore data, rather than just presenting conclusions, can completely change how insights are understood and acted upon.

A key example of this is accessibility in data visualization. Traditionally, blind or low-vision readers get a simple caption describing a chart. While this conveys some information, it limits the user’s ability to explore the data. What if they want to investigate a specific outlier, test a hypothesis, or follow a thread you didn’t anticipate?

Satyanarayan’s group has tackled this challenge by developing systems that let screen reader users navigate visualizations hierarchically. Users can drill from the big picture down to individual data points using just a keyboard. Instead of being told what to see, they have the freedom to explore, and that’s a game changer. Reading about this made me reflect on my own projects: even small design choices can either preserve or restrict a user’s ability to interact with data. Accessibility isn’t just a checkbox; it’s about agency.

Another thing that stood out to me is how visualizations exist in social and cultural contexts. Charts and graphs aren’t neutral: they’re shared, remixed, and sometimes used to mislead. This is especially clear in the age of social media, where visualizations can become stripped of their context. Satyanarayan’s work reminds me that as designers and analysts, we have a responsibility to think not just about the data, but about how it’s consumed and interpreted.

What I find inspiring about Satyanarayan’s approach is the co-design principle. Accessibility isn’t about designing for someone else, it’s about designing with them. Collaborating directly with blind and low-vision researchers ensures tools actually serve real needs. In my experience, this mindset — listening, testing, iterating — can completely transform the impact of a visualization.

And with AI tools becoming more prevalent, there’s an important question: how do we make sure automation doesn’t take away the parts of visualization work we find most creative and engaging? For me, the key is designing systems that amplify human curiosity and agency, not replace it.

Reading about this research made me reflect on my own practice: the best visualizations aren’t just technically impressive, they invite exploration, include everyone, and spark curiosity. That’s the kind of work I hope to continue creating and supporting as I write again for this newsletter.

Before we wrap up, I’d recommend Thinking, Fast and Slow by Daniel Kahneman, a book that completely reshapes how you understand your own decision-making. It’s a fascinating look into the two systems that drive our thinking: the fast, intuitive one and the slow, deliberate one, and how balancing both can lead to better choices in work and life.