The Data Exchange Podcast: Tara Kelly on how data tools continue to reshape journalism.
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This week our special correspondent and editor Jenn Webb speak with Tara Kelly, Data Editor at DataJournalism.com (DJC) an organization created by the European Journalism Centre. DJC provides journalists and media groups with free resources, materials, online video courses and community forums. Most recently they created two free e-books: The Verification Handbook and an updated edition of the Data Journalism Handbook.
Tara Kelly:
I think what used to happen was they’d hire a data scientist and a couple of developers and a couple of designers and they would all try and work together. But now what’s happened is journalists have learned a bit of coding, the designers have learned a bit of coding and storytelling, the developers have learned a bit of design and coding, and maybe the storytelling side, and they’re all working together. So we’re seeing that more and more. I know, The Guardian operates like that, The Telegraph as well.Some news organizations maybe still have that old school mentality. They have a specialist that comes to the data desk, and they see it as like a service like, like you go to the library, and you get a researcher to help you dig out stuff. This doesn’t work so well. Because then sometimes that person, that reporter who did all that digging, doesn’t get a byline, but the one who wrote it does. So we’re moving away from that, thankfully, but there still does exist this “help desk” mentality. The best way to do it is to have a mix of all these skills together, and working together, coming up with the story and, and learning a bit of this and a bit of that.
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Related content:
- A video version of this conversation is available on our YouTube channel.
- Xiyin Zhou: “Detecting Fake News”
- Weifeng Zhong: “Using machine learning to detect shifts in government policy”
- Amy Heineike: “Machines for unlocking the deluge of COVID-19 papers, articles, and conversations”
- Rayid Gani and Andrew Burt: “Auditing machine learning models for discrimination, bias, and other risks”
[Image: Newspapers from pxhere.]