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Statistics Degree Not Required

Stefanie Posavec
How did you get started as a designer, and later, as a data illustrator? I grew up in Colorado. I’ve wanted to be a graphic designer since I was in high school, so when I went to university, I got a BFA in graphic design from Colorado State University and then completed my MA in communication design at Central Saint Martins College of Art and Design in London, where I still live today.

During my masters program, I focused on a project called Writing Without Words, where I explored ways of visualizing writing styles in literature—mainly with Jack Kerouac’s novel On the Road. While I was working with text visualization for my studies, I didn’t think I would end up in this field. I thought I would work in publishing, and that’s what I did: I got a job at Penguin UK—now Penguin Random House—as a book cover designer. I thought I’d be in what I considered my dream job for the rest of my life! But my Writing Without Words project quickly gained a lot of recognition on the Internet, and my inbox filled with requests from people asking me to work with data or information graphics, a field I had never considered. That opportunity would have been a shame to miss, so I quit my job to freelance. I’ve been freelancing for six years now, working with data as a designer with the occasional book project thrown in for good measure.


How is data illustration similar to and different from graphic design? I originally called myself a “data illustrator” to differentiate myself from traditional information designers and data visualizers. I would often visualize data in order to communicate a more subjective, emotive message that went beyond the insights found in the data. I was using data as a material, much like one uses paint, ink and pencil to illustrate and communicate. So I said I was a data illustrator to explicitly state that data visualization, when used in this way, has a different outcome than when it’s used in a scientific or journalistic context.

I was using data as a material, much like one uses paint, ink and pencil to illustrate and communicate.


Over time, I’ve felt less of a reason to use this data illustrator label. I’ve realized that I am just a graphic designer whose favored material is data. I work with data in many ways: to create exhibition artwork, to inform the design of a necklace and even to create interactive pieces where a person can dance through data. All of these out-of-the-ordinary data projects sit alongside the more traditional information design and data visualization projects I also undertake. Both are valid ways of working with data.

These days, there isn’t much difference between working with data and working as a graphic designer in other areas of design. The main similarity is the emphasis on building design systems: data visualization requires the creation of a system of rules for encoding graphic elements with different types of data in a legible, beautiful, flexible way. This systems-based thinking is similar to that used when designing a flexible book or magazine layout and creating a unified set of brand guidelines.

What is it about data that can intimidate people? Speaking from a graphic designer’s perspective, data can intimidate us because we often don’t have the statistical skills to work with it effectively. I learned early on to always collaborate with a data researcher on projects that require statistical knowledge. I’m a designer, not a statistician—why try to be something I’m not and invariably draw the wrong statistical conclusions in the process? Also, I think that communicating data is something that a lot of graphic designers shy away from, which is a shame. Designers are natural innovators: we love the challenge of presenting text or concepts in new ways and communicating metaphors using a variety of creative approaches, so why not apply that same spirit of innovation to communicate numbers, data and information?

What would make a data visualization come up short? When people think that presenting a single number or fact by making it huge and decorating the design with lots of pretty illustrations counts as a data visualization. This could be fine in some situations, but it’s not a data visualization because it doesn’t offer any context about that particular data point. The socially conscious data visualization firm Periscopic outlines this very neatly in a blog post. Also, data visualizations where either the data is lacking in integrity or the visualization was created in order to mislead. Honesty and integrity is critical, regardless of whether someone is using data in an artwork or a newspaper graphic.


When you are designing book visualizations—like you did in Writing Without Words—do you read a book differently than you would if you were designing its cover? I would read the book differently. I—or the computer, since so much of this can be automated—am looking for ways to quantify the text: counting the number of words per sentence, the sentences per paragraph, the paragraphs per chapter, the parts of speech and so on. But it’s also interesting to gather the data that only a human can gather and a computer would struggle with, like plot lines. But I can’t claim to be an expert—this type of manual tagging of texts is something very common for humanities scholars. I like quantifying that which is difficult to be quantified, like themes in a book, because I enjoy the challenge of trying to show human nuance and intuition in a more methodical way while still retaining the humanity found in the data.

What prompted you to begin exchanging hand-drawn personal data with Giorgia Lupi, your pen pal and coauthor for your data project–turned–book Dear Data? Giorgia and I had only met twice in person—at an art festival at the Walker Art Center in Minneapolis, Minnesota—when we realized we had a lot in common, both personally and professionally. We are both only children and expats, and both of us don’t really code, but we work with data in a very handmade, analog way, using sketching as part of our design processes. This way of working is in contrast to how many people often create data visualizations using code and computation; when we realized we worked in such a similar fashion, we wanted to get to know each other better, ideally in this hand-drawn way.

We began to formulate a project idea and decided to use our biggest constraint—living on different continents, with Giorgia living in New York City—as our biggest asset. We came up with the idea of sending hand-drawn data postcards to each other, wanting to answer the question: Can we learn about someone else through her or his data? Each week for a year, we would gather data on a shared topic, then draw that data on a postcard to send to each other.

What did Dear Data teach you about how data can illuminate personal experiences? As we embarked on the project, we noticed that once the postcard arrived at the other person’s address, we would interpret the hand-drawn data visualizations and message each other questions, using the postcards as a starting point for further conversation. In the context of personal experience, we started to see the postcards as a launchpad to describe our experiences—as opposed to definitive answers and truths about our lives. This can be applied to data in general: data is a starting point for discussion and never the whole story.

How has data visualization advanced as it’s become more popular amongst designers? Designers have always, in a way, been “information designers.” The role of an effective book, poster and website designer has been to communicate information effectively and legibly for the given context and audience. And charts and diagrams have been part of our visual language for centuries: all the charts you are used to seeing in a spreadsheet or presentation program—such as bar, line and pie charts—were invented by engineer William Playfair in the eighteenth century. So I wouldn’t say data visualizations are becoming more popular, but since data is ever present—and increasing—in our world today, we as designers will need to work with it.

However, we are in the second stage of this current data visualization “renaissance.” Data isn’t just something to be presented as a traditional visualization or information graphic, but now, it can also be used as a design material, and data visualization can be used in the design process to create subjective, emotive work. I find it fascinating that the same dataset can be used to inform an art piece in a gallery as well as in an academic paper—and that both of these responses are valid in their different contexts.

What advice do you have for a designer who is just starting to dabble in data visualizations? I use three main rules of thumb when working with data:

1. Use data with integrity. Bad data will lead to a bad project.

2. The data informs the form. Let the data determine the visualization method instead of forcing data into a predetermined form.

3. Everything must have a reason. As in communication design, this rule applies to data visualizations as well, but more critically. Since every line, color and shape can represent data, if design elements don’t have a reason, they could confuse the viewer!

How will the rise in big data usage across many industries affect the general field of graphic design? The recent advances in computing have meant that the world is producing more data than ever before, so more and more designers have been needed to parse, communicate and make sense of this data. As time moves forward, there will be no distinction between a communication designer and an information designer/data visualizer; this currently separate field of data visualization will be considered an essential skill for a communication designer. So many design students now have modules on information design and data visualization. I definitely didn’t have these resources when I was studying design at university!


Stefanie Posavec is a designer whose favored material to work with is data, with projects ranging from data visualizations and information design to commissioned data art. Her personal work focuses on nontraditional representations of data derived from language, literature and scientific topics, often using a handcrafted approach. Posavec’s work has been exhibited internationally at major galleries including the Museum of Modern Art (New York); Centro Cultural Banco do Brasil (Rio de Janeiro); the Science Gallery (Dublin); and, in London, the Victoria and Albert Museum, the Science Museum, London, the Southbank Centre and Somerset House. Posavec recently completed a year-long drawing project with New York–based information designer and artist Giorgia Lupi called Dear Data, for which they gathered and drew their data on a postcard to send to each other every week. This project was deemed the best Data Visualization Project and the Most Beautiful—the highest accolade—at the Kantar Information is Beautiful Awards 2015, and a book of this project has been published by Particular Books, an imprint of Penguin Random House UK, and the New York–based Princeton Architectural Press. Originally from Denver, Colorado, Posavec now lives in London, United Kingdom.

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