The history of data journalism
Conversations with Data: #88
Do you want to receive Conversations with Data? Subscribe
Welcome to the first Conversations with Data newsletter of 2022!
There's no question that the future of data journalism is bright. But where did it all begin? Veteran journalists Brant Houston and Stephen Doig share their firsthand experience of working in the early years of data journalism.
The pair identify the key data journalism stories and books that shaped the industry. We also hear what is next for the field and some helpful advice on making it in data journalism.
Professor Brant Houston holds is the Knight Foundation Chair in Investigative and Enterprise Reporting at the University of Illinois. He is also the editor of the online newsroom at Illinois, CU-CitizenAccess.org.
Stephen Doig is a journalist, professor of journalism at Arizona State University, and a consultant to print and broadcast news media concerning data analysis investigative work.
What we asked
Talk to us about how you two met.
Brant: Back in the 80s, I was working on a story that required me to use Statistical Software. I called up Steve to ask him a question about it. Later we met up at conferences and spoke. There were very few people doing data journalism at the time. It was a lot like rock n'roll. However, thanks to NICAR and the Investigative Reporters and Editors network, there was a very collaborative and cooperative feeling among fellow journalists working with data. It was always word of mouth because you didn't know who was working on what.
Brant, you wrote a piece for DataJournalism.com on the history of data journalism. Give us a brief overview.
Brant: Someone from The CBS Network got a bright idea that there were computers, and if you fed in a bunch of data into the computer, you might be able to predict who won that election that year before all the results came in. From what I could tell from my research, they had a pretty good idea of who won. It was Eisenhower. But they froze. They were like, "We're not sure if we're right. This is taking a big risk." That was what I call the false start.
If you jump ahead 15 years, you get up to reporter Philip Meyer really taking apart the assumptions of what caused a race riot in Detroit. Local Detroit folks said it was all these outside people who came in. But it turned out no, they had problems within the city and the people rioting were actually people who lived there. Another start was Philip Meyer's book on precision journalism. That's when things really started rolling.
What are some of the most defining pieces that shaped data journalism?
Brant: Philip Meyer's Detroit riot story was remarkable. Elliot Jaspin's piece on the school bus drivers and criminals also moved the industry forward. I would also include Steve's 1992 story on Hurricane Andrew. Through mapping, it showed how lax zoning, inspection and building codes had contributed to the destruction. The colour of money on mortgage discrimination done by the Atlanta Journal-Constitution was also a breakthrough moment because the field was getting recognised for what it could bring to investigative journalism.
Steve: The Atlanta Journal-Constitution mortgage story was a Pulitzer-Prize winner that had a huge data element to it. It made editors sit up and pay attention. It also helped catch the attention of all those other investigative reporters out there who were used to looking at documents, shoe-leather reporting and interviewing. They saw data as another tool they needed to learn.
How do you believe COVID-19 has impacted data journalism?
Brant: I think the pandemic has helped people know the revolution is here and that it's occurred. I think it's been a great marketing campaign for why journalists should use data. It's completely global now, and when you suddenly get a global pandemic, everyone can see all these journalists are using data. It may encourage many others to use data, but I think it's been waiting for somebody to advertise the power and importance of this reporting. And here it is. It's data every day, a visualisation every day.
Steve: I would say 20 years before the pandemic came along, we were already at the point in data journalism that any serious newsroom had people like Brant or me doing some of this. In the 80s and 90s, innovation in data journalism was happening in mid-sized metros like the Miami Herald and the Atlanta Journal-Constitution.
National newspapers like The New York Times were much slower. When they needed to do a data-led project, they would hire a consultant. But at some point, The New York Times looked around and said, "Hmmm. We need to get some of that." So they cherry-picked from great teams all around the country and brought them all in. They were instantly able to put together a fabulous data journalism team. I think the pandemic has raised the visual visibility of data journalism, not only within the newsroom but also to the consumers.
Both of you are professors who teach data journalism and have worked in the field. What advice do you have for those starting out?
Steve: The thing I try to get across to students is don't feel like you have to have mastered it all to start doing it. Get out. Pick an easy thing like a daily story where all you need to do is put something in a different order. And if you have learnt how to get your list into excel, you hit the sort button, all of a sudden you started doing journalism. You moved it from the boring alphabetical order into the best on the top and worst on the bottom. Suddenly, there is journalism at each end of it. My advice is don't be intimidated by it. You'll grow additional skills when you need them. You don't have to master it all to get started.
Brant: One of the approaches I have is to start with the story. Journalists are so busy and hyper. They want things to be applied as quickly as possible. So Steve's suggestion that you put something into columns and rows and put it in a different order to see the story is a great idea. Some journalists love numbers, and they're going to find lots of stories. But for someone who's very busy, my suggestion is to find a story with a database and see if it helps you.
What technologies are you most excited about?
Steve: I think the tools will continue to proliferate to deal with problems. A tool to deliver better text analysis still hasn't been created yet. We'll be able to essentially read a long text and find deeper patterns in it. Transcriptions and translation software have both improved. Another technology I'm excited about is virtual reality. In science fiction movies, you see a person sorting through data that's floating in front of him. I think that we may start seeing some of these patterns once virtual reality matures. Another is augmented reality where a reporter is out in the field wearing glasses. Somehow they are able to access additional information about the thing covered right there and then, and readily available.
Brant: Steve is right about the need for better software when moving unstructured data to structured data. Another thing that is happening in the industry is artificial intelligence. We're getting more sensible about how much we can do or not do with it. It's going to get better. Throwing algorithms at vast amounts of data to help us see possible patterns will help. Of course, we still have to have a journalist with brains looking at what comes through. But I think we will see a lot happening with A.I. that will aid and abet us. The other part that will be exciting, but maybe difficult, is how we translate a lot of what we're doing to the starting point on a mobile phone or mobile device. The question is how do you present data on a smaller screen in a more effective way? And how do you make that data even more interactive so that people can be informed by the data?
What other innovative tools are moving forward in the field?
Brant: There's a lot of innovation in the presentation of data, but I've always been fascinated with how you gather the news -- using the data, using these tools. I think we'll see a lot more integration with people in the field going and feeding back into a database and the database feeding back to them too. This is something that happens in the utility industry all the time where there's the mothership back at headquarters and the utility guys are here and they're doing stuff there. I can see speeding that process up while reporters are in the field.
Steve: That brings up sensor journalism, the idea of having access to live data that is being gathered -- not just CCTV every 10 steps in London. I'm talking about weather sensors, all the little devices that are scattered around your city that are capturing the air quality, the temperature and the noise levels. It will become even more important to be able to pull that data in and produce useful information for finding or telling stories. The technology is cheap enough now for newsrooms to use their own sensors and handle the data collection. This will become easier to measure over time.
Latest from DataJournalism.com
How can we use data to create stories that resonate with audiences and make a difference? In our latest long read, Sherry Ricchiardi explains what we can do to humanise data and give a voice to the people behind the datasets. Read the full article here.
There's no question that the future of data journalism is bright. But where did it all begin? Professor and veteran journalist Brant Houston provides a historical look at the field from CBS News' attempt to predict a US presidential election up until today. Read the full article here.
Tara from the EJC data team,
PS. Are you interested in supporting this newsletter or podcast? Get in touch to discuss sponsorship opportunities.
If you experience any other problems, feel free to contact us at firstname.lastname@example.org