Cosmic Design

In Conversation with Netherlands-based data artist Nadieh Bremer

Artwork from Bremer’s Anhedra collection

You trained in astronomy before moving into data visualization. What ways of seeing or thinking carried across that transition, and how do they still show up in your work today?

One of the main things that got me interested in astronomy as a child was seeing the amazing photos that Hubble took of the fascinating objects out in space. I think that these photos in a way still influence the design style that I apply to my visuals — at least, I’ve heard this from several people in the past, that they can find a space-like theme throughout many of my works. I also think that the general way of thinking and working with data that I learned with astronomy plays a major role in my work.

I’ve always seen data as a treasure trove, almost like a chest full of potential for interesting stories and new things to learn that is waiting to be found. Not as something to be scared about. The more data, the better, at least for me. And I still prefer working for clients with large, diverse and complex datasets, because those are the ones that generally have the most interesting insights and give me the most “tools” to create my visualizations with in a way that is also intriguing and visually appealing.

Your visualizations often rely on connected, radial, or spiral structures rather than standard chart forms. When you choose those geometries, what kinds of relationships or signals are you trying to keep visible?

When I start working on a design for a new visualization, often after having first done an analysis of the data, to know what information it holds, I always try to only think of the data and the goals. What variables do I have at my disposal? How much data? And what is the goal of this visual? Should people learn something from it? Or be moved emotionally, when the aim is more data art. And who is my audience and in what medium will the final visual appear — a large poster? Aimed at mobile screens?

It’s with this information that I go and sketch my designs. Do I want to show connections? Then I’ll probably start sketching some dots connected by a line and work my way up to something more detailed from there. My point is that I don’t try to think in chart types. I try to think about the patterns, stories and information that I want to reveal visually.

The fact that I also often end up with radial layouts is that this is something that I often find makes the visual look aesthetically pleasing — for example, humans like circles. It is not specifically driven by a certain signal I want to convey, but more an aesthetic choice. It won’t work with every type of dataset or goal, but I often find myself coming up with radial-based layouts during the sketching and design phase.

In Data Sketches, you and Shirley Wu made the process itself visible — including constraints, drafts, and pivots. Looking back, was there a moment where a small decision had an outsized impact on the final outcome?

Gosh, it’s been nearly 10 years since I worked on Data Sketches with Shirley, so some of the details have definitely faded away. Thinking about it, I feel like there are many small decisions that can have a large impact, especially in the beginning when we were thinking about ideas to visualize. The earlier in the process, the more impact a decision might have.

For the “Myths & Legends” month, there was first an idea to do something with a dataset on the various tellings of the Cinderella story. But eventually a different idea, on how people have seen their myths and legends in the night sky through constellations, is what I created. It is also often driven by the availability of data.

For the Nostalgia month, I knew I wanted to do something about Dragonball Z, a show I was a big fan of during my teens. I started looking online as I didn’t know what exactly I wanted to visualize. There I found that the Dragonball Fandom pages contained all of the fights that occurred in every episode. I immediately knew that that was the perfect dataset and could see how I would visualize all of the fights that the characters of DBZ had fought in over the seasons and sagas.

During the visual creation there were also surely cases where small decisions had big-ish impacts — for example, the Olympic Feathers project is named such because originally I had created feather shapes at the end of each sport slice, but those shapes didn’t make the final cut, but never quite so big as defining the concept and the impact that the specifics of the dataset had. The Data Sketches book that we wrote about it will surely contain every one of the small decisions with large impacts though.

You’ve spoken about wanting your work to evoke emotion and remain memorable. How do you think about the line between emotional resonance and ethical responsibility in data storytelling?

I think the most important part to always be mindful of is to make sure that you’re not wrangling the data to show something that isn’t in there. In that sense I don’t see a line between emotional resonance and ethical responsibility. They live on different axes. What you’re doing to make sure you’re trying to convey the data in an ethical way does not mean it can’t be emotionally resonant. In fact, I find that the data stories that are aimed at touching your emotion are often also the ones that make you think, that often have a theme of showing how the data isn’t perfect. See, for example, the installations that Shirley Wu has been working on for the past years.

In your data-art collections, the work is often meant to be experienced as much as interpreted. What shifts in your process when you’re designing for feeling rather than explanation, and how do you know when a piece is complete?

When I’m creating data art I’m thinking much more about the concept behind the visualization and much more about the visual aesthetics of the piece. For example, for a piece on what people eat, their diets, I had data about the ingredients that tens of thousands of people had eaten in 24 hours. The concept that we went for was to show each person’s ingredients translated into a different mark for 25 different food groups as a ring. Each person had its own ring, but each at a random radius. All of these rings together created this kaleidoscope of circles, reminiscent of a plate of food as seen from above.

Also connected to the idea that people, and the food they eat, are created from base ingredients, but combined they come together and form something much greater. For a project for UNICEF about schools and children, I turned each school into a little decorated square, combining to create little kingdoms, always keeping in mind that I wanted the final visuals to evoke this sense of childlike wonder.

I quite like working in data art pieces, because I can let go of visual elements that have to clearly convey the data and use more innovative ways to turn my data into visual elements, even if you can’t make out what “number” the data was. I can truly focus on the idea and the visual execution, to make it stand out and memorable to an audience.

Knowing when a piece is complete is complex. For some pieces, I feel like I can never get it quite right. I can’t put my finger on it, and I can’t think of ideas of making it better, but I’ll simply have to be okay with the fact that “this is as good as I’m going to get it.” For other pieces, I can only say that it feels right. I’m happy with it, my eyes want to look at it, and again, I would not have any remaining ideas on what I would change.