This website protects your privacy by adhering to the European Union General Data Protection Regulation (GDPR). We will not use your data for any purpose that you do not consent to and only to the extent not exceeding data which is necessary in relation to a specific purpose(s) of processing. You can grant your consent(s) to use your data for specific purposes below or by clicking “Agree to all”.
European Journalism Centre in conversation with data experts at #ijf18 in Perugia
The EJC is heading to the International Journalism Festival (IJF) in Perugia this spring with its Data Journalism Handbook to discuss data and society.
In the midst of planning our session Conversations with data (Friday 13 April, 16:30–17:45, Centro Servizi G. Alessi, Perugia) we caught up with two of our guest speakers, Lam Thuy Vo from BuzzFeed News and Gregor Aisch from Datawrapper and asked them about their take on the current state of data journalism and tips on how to keep up with this ever-evolving field.
Gregor: When I started doing data journalism projects around 2010, there was a lot of hype around an almost non-existing field. There had only been a few data journalism projects and you could count the full-time data journalism positions in German newsrooms on one hand. Now it looks like the big ddj hype is over, but the good thing is that you see more and more data journalism projects and more and more dedicated data teams. In 2010 all you needed was a dataset and an interesting visualization or map, now there is a lot more competition and the projects get more sophisticated.
Lam: There are a lot more resources and specializations in the field of data journalism now with varying degrees of technical, visual and editorial expertise. It’s also a much more communal space than it used to be.
How would you describe the current state of data journalism? What are the biggest challenges, accomplishments — and: In which direction will data journalism steer towards in the next years?
Lam: Data journalists are more creative than they have ever been often finding new ways to unearth and create data sets beyond what government summary tables offer. I do believe that one of the biggest challenges is a diversity of perspectives in data journalism which often comes with hiring, furthering and giving resources to journalists from different backgrounds. Newsrooms are bad at representing the population they cover — and data journalism as a field is no exception. Percentages of ethnic minorities and immigrants in newsrooms is never on par with the percentage of ethnic minorities and immigrants who are part of the general population. My background as the daughter of a refugee and a first generation immigrant to the US deeply informs how I view statistics and data.
Gregor: I think data journalism is in a decent shape right now, mostly because nobody is talking about it anymore and people are just doing it. One ongoing challenge is to also apply it to areas that are not inviting journalists with ready-to-use datasets. It’s easy to do ddj projects around elections and big sport events, where you get nice structured tables or historical data. But it’s harder to do it on subjects with little or no data. That’s where data journalism quickly becomes as resource consuming as traditional investigative journalism and believe those kinds of projects will become increasingly important.
The handbook’s premise is that we should start looking beyond best practice cases and start reflecting on what could have been done better. Where do you see room for improvement in the data journalism sphere?
Gregor: Sounds like a good plan. One thing that I don’t like about some of the best practice cases is that it’s so easy for newsrooms to just say “Well, that’s nice but we don’t have this kind of resources here” or “We’re not the New York Times”. Data journalism isn’t something you need a lot of bodies to do.
Lam: I deeply believe in educating, hiring and helping people from different backgrounds enter the field of data journalism and believe that people with vastly different experiences produce better and more varied journalism.
Lam, you are also one of our Data Journalism Handbook authors. Could you describe the context of your topic and who can benefit from it?
Lam: I will contribute chapters on mining social media data for storytelling. Journalists interested in the intersection of technology and society and political accountability reporting may find it useful to know about social media data.
What are your tips for other (data) journalists to keep up in this ever-evolving field?
Lam: Take things in step by step, be kind and forgiving to yourself and understand that acquiring the skills necessary to succeed in this field are incremental. Nothing comes overnight but there’s a vast community out there that is paving the way, sharing their code and happy to help.
Gregor: The key to keeping up is to spend a lot of time with people who are smarter than you. If there are good developers in your newsroom, you want to be sitting next to them. If not, your newsroom is doing something wrong and you should probably consider finding a better environment.
Finally, it’s really hard to do projects on your own, and it is equally hard to do projects in a eleven people committee in hourlong brainstorming sessions and project meetings. But if you find yourself in a team of two or three dedicated data journalists, you can do almost anything!
This second edition of the Data Journalism Handbook is being produced by the European Journalism Centre and Google News Lab, with support from the Dutch Ministry of Education, Culture and Science and edited, like the original, by experts in the field Jonathan Gray and Liliana Bounegru at the Public Data Lab. The Handbook will be available as a free open-source download on datajournalismhandbook.org in Autumn 2018.
To get chapter previews and exclusive news about the Handbook before anyone else, join our mailing list here. You can also get in touch with us directly at email@example.com or use #datahandbook to get our attention on social platforms.