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Star Tribune editor strives to teach coworkers and readers about data

By Aidan Connolly
University of Nebraska-Lincoln


MaryJo Webster, data editor at the Minneapolis Star Tribune

When MaryJo Webster walked around the newsroom at the Minneapolis Star Tribune and showed a set of visualizations about foster care discrepancies to her coworkers, their jaws dropped.

As a data editor at the Minneapolis Star Tribune, Webster was working with other reporters to find out why Minnesota has more American Indian children in foster care than any other state.

Only six of 1,000 white children in Minnesota are in foster care, while 96 of 1,000 American Indian children in Minnesota are in foster care.

Rather than list the numbers, Webster helped put together a visualization. She thought it was more effective that way.

“Everyone I talked to said we needed to tell the story visually with charts to introduce readers to the issue,” Webster said.


Webster’s graphic for the Star Tribune’s story about American Indians in foster care caused her coworkers’ jaws to drop.

The article ran with the visualization above the headline. It conveyed the main point of the article in a digestible format.

Webster said good visualizations have a key point that stands out.

“[Readers] don’t have to read the text,” Webster said. “They don’t have to zoom around or spend a lot of time on it. It should jump out at them.”

Webster said the best way to have a strong key point is to make sure only the relevant information is used.

“It’s like when you’re a young reporter and you have all this stuff and your editor says you can only use half of it,” Webster said. “It you start throwing all that stuff in, at some point it becomes overwhelming. You have to whittle it down.”

Webster described her job as unique in a newsroom.

“There’s really no one else doing what I do,” Webster said.

Along with editing copy, Webster edits visualizations, looking at how they are displayed and whether they are effective. She also produces some data-driven content that is edited by her coworkers.

Webster hasn’t always been an editor. She started as a reporter at a small-town newspaper in New Ulm, Minnesota. After discovering data journalism, Webster went to the University of Missouri to learn more.

Webster worked for multiple organizations after earning her graduate degree, including USA Today and the St. Paul Pioneer Press before ending up at the Star Tribune.

As for her typical day, Webster said she doesn’t have one.

“The beginning of my day is looking at my to-do list and prioritizing,” Webster said. “Then, I just dive into things.”

One recurring project for Webster is the Star Tribune’s “Data Drop.” Webster said the purpose of the Data Drop is to tell stories using primarily data visualizations.

It also allows Webster to work with other reporters who are interested in gaining data skills.

“I use it as a teaching opportunity for reporters who want to get their feet wet,” she said.

Webster has to constantly learn new things herself. Because data journalism relies on technology, things often update or change.

“I’ve probably retaught myself every couple of years,” Webster said. “Data journalism is moving faster than the rest of journalism, I think.”

Along with coworkers adding to their personal toolbox, Webster benefits from the data education.

“There are so few people in the newsroom who know what I do or could be a backstop for me,” Webster said. “It’s nice to go to someone and ask for feedback.”

For young journalists who are trying to get into the industry, Webster suggests they look into data journalism.

“It’s the best place to be in journalism right now,” Webster said. “It’s the safest and has the most job opportunities.”

However, good data journalists need to be good journalists first, Webster said.

“You need to be able to wrap your mind around the big picture and also think about the details,” Webster said. “Some are good at one or the other, but data journalists need to be good at both. That’s hard.”

Once the basics are mastered, Webster said the next step is to start getting comfortable with data. She has a collection of learning materials on her website.

“It’s akin to learning a foreign language,” Webster said. “You have to progress through it. You’re not going to be able to master all of these things immediately. It takes time.”



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