“The focus of data journalism shouldn’t be to wow, but to inform,” said Mona Chalabi, this year’s Case Western Reserve University ShowCASE guest speaker, in her noticeably British accent.
Chalabi is The Guardian’s data editor, a data journalist at NPR and an important advocate for the responsible use of data. Chalabi has also worked for powerhouse organizations like the United Nations, Transparency International and FiveThirtyEight.
According to Chalabi, working at these different organizations helped develop her understanding of data.
“All these experiences really inform[ed] the way I think of numbers,” said Chalabi.
Now, Chalabi sees her role as taking numbers and making them approachable using pictures. She is interested in preventing people from being “bouncers,” her term for those who look at a website for a few seconds then leave. Visuals slow a reader down and can get them engaged in the information.
Chalabi’s work couples art with information and ties into culture. She described the goal of each of her works as linking the image and the topic together.
“It is this idea of marrying the subject with the visualization,” she said.
She draws most of her graphics by hand, which has its challenges. Chalabi believes people inherently trust computer graphics more than hand-drawn graphics, saying, “we have a trust that is almost worrying in computer graphics.”
Chalabi also believes the public is distrustful of statistics in general. Bad data journalism is a big part of this problem, according to Chalabi. Specifically, Chalabi noted that public distrust comes from recognizing incomplete or misleading data usage.
Even good data journalism often cannot capture the public’s attention. Chalabi operated a fact checking column after the last presidential election that she believes was more effective than other similar columns because she showed her readers why and how something was inaccurate.
“That process of bringing someone along is really critical,” said Chalabi when describing effective data journalism.
Chalabi also provided several other essentials of effective data journalism. Sequencing and the element of surprise are important for a data journalist to consider, because effective usage makes visualizations even more powerful. According to Chalabi, not being afraid to scrap something and start over is also an important attribute of a data journalist.
Knowing the audience for a visual is also a critical consideration Chalabi has to make. Chalabi described how images have a lot of significance, so making mistakes is especially problematic. Additionally, Chalabi has to be careful because issuing a correction for a visual is more difficult than issuing one for text.
Although Chalabi believes many people balk at the difficulty required to turn relative inaccessible data into an effective visualization, she believes her work is important because she can affect real change.