Data tells a story, and when it’s in the hands of Mona Chalabi, data editor for The Guardian U.S., the tale can be riveting. The London-born, New York–based journalist of Iraqi descent has made a career of creating striking visualizations that highlight unexpected issues ranging from female hair-removal to anti-Semitism in Europe, which have been shared as many as 2.2 million times on her personal Instagram account. Recently, she has garnered attention for depicting statistics related to the novel coronavirus and police brutality targeting Black people in the United States. Here, Chalabi—who has also hosted and produced Strange Bird, a Guardian podcast on how numbers shape our lives—talks about bias in data collecting, how she developed her signature style, and why she makes graphics for her least-informed reader first.
While studying for a master’s degree from the Paris Institute of Political Studies, Chalabi took a position with the International Organization for Migration, where she compiled information on topics such as the number of Iraqis displaced within the country and those who’d become refugees. Though she enjoyed the work, she didn’t feel that it had much of an impact. “We’d work for months, and [our reports] would be read by 10 people. That was frustrating,” she says. After a one-day workshop on data journalism presented by an editor at The Guardian, however, she grew inspired by the potential of numbers to communicate information. Chalabi stayed in touch with him and soon started interning at the paper while freelance writing to make ends meet. Her persistence paid off: She was eventually offered a full-time position at the paper, in London. Soon she took another risk, moving to New York to join the then nascent media startup FiveThirtyEight. She quickly regretted the decision, feeling that her work was going unrecognized and her ideas were often being dismissed. (FiveThirtyEight declined to comment for this story.) In retrospect, Chalabi attributes this to being a woman of color in an environment that was largely white and male. “There was nothing I could have possibly done to convince the editors of my worth,” she says. It was during this period that Chalabi started drawing by hand with colored pencils as a creative outlet for her frustration. She began illustrating data-visualization projects to contrast with the more traditional computer-generated graphs and charts on the site. She further developed her signature style, which combines computer graphics and freehand drawing, when she returned to The Guardian, in 2017. “I started regaining my confidence and trusting myself.”
The numbers tell the story, but she helps: Mona Chalabi’s hand-drawn graphics address hot-button issues directly, yet artfully. Lines can look imprecise for a reason.
Make your point
Chalabi creates her graphics for the broadest possible audience, taking pains to make them easy to grasp by her more than 400,000 followers on Instagram, and not just “highly educated people,” she says. Recently, she has gotten involved in activism, making posters—displayed by volunteers along the Brooklyn Bridge—outlining statistics related to government spending on the NYPD. And while many data-viz creators take pride in simply presenting information in a digestible way so that readers can draw their own conclusions, Chalabi interprets the numbers to tell a story. “I don’t even pretend to be objective,” she says. “Part of journalism isn’t just informing people but giving people tools to act on information. Hiding behind objectivity feels like negligence,” she continues. “I’m always trying to find ways, as well, to say, ‘If you care about this, go vote here.’ ” To source data, she relies on nonpartisan organizations such as the Census Bureau, as well as academic studies and reports from nonprofits, but she is always conscious of what’s missing in the research. “Data gathering is a reflection of existing systems, and it can be manipulated to serve a purpose,” she says, adding that she always looks at the demographics involved in a study and asks herself whether there are any outliers in the data. Her creative method—she often plots data out precisely on a computer before drawing over it by hand—evokes this: “On a computer, data looks slick. I draw over it to show that data isn’t always precise. The lines aren’t completely straight to show that there is a margin of error in all data sets.”
Get it right
Chalabi can get nervous about negative reactions to her work online. “I constantly think, before I publish, This is going to be the post that will get me canceled.” To quell her fears, and avoid making mistakes, she seeks feedback from editors and stays open to criticism. She even started a Patreon account to offer readers a peek at her process and build a community she trusts to give her feedback on early drafts. “My work often deals with sensitive subjects,” she says. If commenters on Instagram point out a mistake, as they did with a chart she made on gendered languages, she will often take the post down and repost a version with a caption explaining her changes. “I am always open to the possibility of being wrong,” she says.