Q&A with Simon Rogers
Conversations with Data: #48
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Simon Rogers is a leading voice in the world of data journalism. From creating the Guardian's datablog in 2009 to now serving as data editor at Google News Lab, we spoke with him about the 2020 Sigma Awards and how data journalism has evolved over the past decade. He also discussed the emergence of machine learning in the newsroom and why collaboration is the future of data journalism. You can listen to our entire 30-minute podcast with Simon on Spotify or SoundCloud. Alternatively, read the edited version of our Q&A with him.
What we asked
Tell us what's happening at Google. Anything new?
I work on the Google News Lab. Our team serves as an editorial bridge for the news industry. We're advocates for the news industry within Google, but also the place where people come to get data and to tell stories. We also produce content and do training. My focus is around data and newsroom innovation. We're very busy at the moment given we're in the middle of a global pandemic. Trends data is a very useful way to understand how people are thinking about this. Currently, we are looking at how we can help journalists around data, innovation and machine learning.
Let's talk about the Sigma Awards. How big was the turnout in the end?
We had 510 entries submitted from 287 organisations across 66 countries. We thought if we received 100 entries, we'd be happy. What I love about the Sigma Awards is it comes from the community. We're lucky enough to be the position that where I work could fund it for the first year, which is great to get it off the ground. And the response amongst the industry was just brilliant. We had people entering from all over the world. It wasn't just the usual suspects from the big newsrooms. We had sole practitioners in developing countries as well as not for profits and designers.
Amongst the winning entries, there were quite a few collaborative projects. Do you think we're going to see more of that in the future?
I do, actually. I think part of that is because data journalists tend to be more collaborative than reporters in other fields. I genuinely believe that is because often we work on our own. There is an isolation to being a data journalist. When you can work with others you can make your work a lot better.
For instance, ProPublica's Election Land Project and Documenting Hate, are great examples of mass collaborative cooperative projects. And then you're seeing projects like The Troika Laundromat, or Copy, Paste, Legislate, where people have different specialisms or geographic areas. Those mixed skillsets can help you to produce a project together that's much better than doing it individually.
Many of the winning projects this year had a mix of traditional journalism with the latest technologies. How do you explain that phenomenon?
I think that the combination of traditional reporting and data reporting is really interesting. We're also seeing that data journalists are now working out how to use machine learning. That took a little while because it's not instantly apparent how to incorporate machine learning into your work. We've seen that with Peter Aldhous at BuzzFeed. Journalists are realising this is a really great reporting aid and it can help make our work better. Also, data journalism is pretty established now. It's a part of every newsroom. So I think that makes a difference.
Does Google News Lab have any training available on machine learning?
Yes, we took part in the MOOC with the Knight Center for Journalism of the Americas at the University of Texas at Austin last year. It's still online and there are sessions on machine learning for beginners by Dale Markowitz. So that's definitely worth checking out as a good starting point. We also did a session at NICAR with Anatoliy Bondarenko. He listed a number of resources in his tip sheet to help get people started.
What does it take to make these collaborative projects work?
The best ones that I've seen give people the freedom to explore and innovate and then come together when it makes sense. We see a lot of parallel projects where you have three organisations working together. But actually, all they're doing is sharing the data and then they go off and do their own thing. But other things like Documenting Hate where everybody is working together with the public, to me, that's honestly more enticing and interesting. I love the idea of these giant collectives of reporters coming together to try to build something that's much stronger than they could do individually.
With the coronavirus (COVID-19) pandemic spreading, have data journalists shown their value in the newsroom?
I think so. It's obviously the great irony that most American data journalists were at NICAR and are now self-quarantining at home after becoming exposed to the virus. Data journalism has had these moments that have made it more important. For instance, the original WikiLeaks releases was an example of that where data journalism was the only way to interpret that. And I really feel it's so important and valuable at the moment. One thing I see looking at trends data is how much people want reliable information. They want to know what the facts are and to understand stuff better. One of the biggest conversations this week has been around flattening the curve. How many people now are looking at epidemiological curves and understanding them now because of data journalists? So, it's super important and really powerful. And it's great to see.
Data journalism is a rapidly evolving field. What direction do you think it will take next?
Reliable information has never been as important as it is now. I think people are aware of that. When data journalism took off in the 2000s, lots of people were doing it. Then there was a period where it became the big people and large newsrooms focusing on it. And now I feel like it's turned around with one or two people doing really interesting things in small newsrooms around the world. That is a trend I'm very excited about. I can't wait to see how The Sigma Awards look next year.
Other happenings on DataJournalism.com
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Our next conversation
With the coronavirus (COVID-19) rapidly spreading, many journalists are looking for ways to visually explain what is happening and how it is affecting the world. That's why in our next podcast and newsletter, we'll be talking to an infectious disease expert about the do's and don'ts for covering this global pandemic. We'll also ask for their top tips and resources for improving your maps, charts, and graphs when communicating about this critical health issue.
As always, don’t forget to let us know what you’d like us to feature in our future editions. You can also read all of our past editions here.
Tara from the EJC Data team,
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