Data Journalism Handbook 2: AMA with Jonathan Gray and Liliana Bounegru

Conversations with Data: #16

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What. A. Week.

We know it’s only been a few days since our beta Data Journalism Handbook 2 was launched, but we’re excited to interrupt your reading with a special edition newsletter to celebrate its release.


From its humble beginnings at MozFest in 2011, the Data Journalism Handbook has come a long way to serve as both textbook and sourcebook for what was then an emerging field. It’s been downloaded over 150,000 times, translated into over 12 languages, and helped countless journalists embrace data in their reporting.

But data journalism is no longer emerging. So, in this new edition, our editors, Jonathan Gray and Liliana Bounegru, challenge us to critically reflect on what the field has -- and could -- become.

We gave you the opportunity to quiz them on the second Handbook and (potentially) suss out what’s in store for the full release next year. Let’s see what they had to say.

What you asked

Naturally, a lot of you were interested in the difference between Handbook 1 and Handbook 2:

Why another Data Journalism Handbook?

“We were really lucky with the previous edition, which seemed a good fit for the moment in 2012. It has been widely translated and adopted as a core text on data journalism courses and trainings around the world. We designed it to age well, providing not just practical guidance on how to work with data, but also a diverse snapshot of the hopes and practices of data journalists at that particular moment in time.


Translated versions of our first Handbook

The field of data journalism has travelled a long way since 2012. Not just because of more sophisticated technologies, but also because the social, cultural, political and economic settings of the field have changed. We’ve seen not only major initiatives like the Snowden leaks and the Panama Papers, but also debates and controversies around the role of data, platforms and digital technologies in society. Lots of tough questions have been raised about what data journalism is, who it is for and what it might do in digital societies.

Rather than just having a narrower focus on data practices, we take a broader look at these questions and consider what we might learn from them. In parallel to doing the first edition of the Handbook, we’ve also gone through our graduate studies and into universities where we’ve been researching these kinds of questions about the societal implications of digital data, methods and platforms. The new edition of the book is our attempt to make sense of the field of data journalism and its changing role in the contemporary world, thinking along with a diverse mix of practitioners and researchers.”

What has the evolution of the data journalism landscape meant for you as editors?

“To use a metaphor: there was a time when the number of readily available books in the world was small enough that it was not considered crazy for a librarian to try to build what they could consider a pretty comprehensive collection of books. Their acquisitions policy could just be: ‘whatever we can get our hands on’. In 2012, it might have not have seemed so crazy to, for example, have a go at making a list of data journalists and their projects from around the world. One very practical consequence for us as editors is that we cannot kid ourselves about our partiality: can only hope to cover a comparatively small number of the projects, practices and themes in this ever-growing field, and it was a difficult job to decide what to focus on in the book.


Jonathan and Liliana working hard on the second edition

Also, as we’ve mentioned above, there have been many debates and controversies about the role and status of data journalism, which we’ve sought unpack and address in the book, as well as examining its relation to other developments. Since 2012 we have seen the rise of questions about the societal implications of technology precipitated by actors, events and issues as diverse as Snowden, Trump, Brexit, Bolsonaro, Xi Jinping, the Syrian civil war, Cambridge Analytica, Gamergate, #metoo, #IdleNoMore, Black Lives Matter, strikes and walkouts from tech workers, Uber riots, the European refugee crisis, Facebook’s News Feed algorithms, “fake news” and misinformation, the Gab platform and the rise of far-right populism and extremism. Several chapters in the book suggest how data journalists might attend to and position themselves in relation to such phenomena.”

On that note, how do you think data journalism can help respond these questions, particularly around the use of algorithms and development of fake news?

“While this is a fast-evolving area, there are many ways that (data) journalists can respond. One of the areas that we’re particularly interested in is how to report on not just content, but also its social life and how people share, interact and make sense with it, including the platforms and infrastructures through which it circulates. We’ve provided several ‘recipes’ for digital methods investigations into ‘fake news’ in our recent Field Guide to ‘Fake News’, which has led to collaborations with BuzzFeed News and others. There’s a dedicated section in the Data Journalism Handbook on investigating data, platforms and algorithms.”


Nick Diakopoulos on his chapter, which helps journalists investigate algorithms

Will the Handbook provide information on tools to help journalists undertake this kind of reporting?

“The Handbook does not focus on tools as such. Specific tools enter the story insofar as they are relevant in accounting for different projects or practices. So this made it less difficult from an editorial perspective as we haven’t had to decide about tools, but instead have invited contributors to talk about different projects, practices, methods and settings - and tools have entered into these stories.

This is not, of course, to underestimate the importance of taking tools seriously. As our colleague Bruno Latour puts it: ‘Change the instruments, and you will change the entire social theory that goes with them’. The choice of whether to use a spreadsheet, a relational database, a network, a machine learning algorithm or a visualisation tool to work with data can shape what you notice and attend to, and the way you think about the phenomena you are investigating. We’re currently working on a research agenda at the Public Data Lab examining and comparing network practices in different fields -- including their narrative capacities in journalism. Several chapters in the book look at techniques, and some look at the use of particular tools. But tools as such have not been the editorial starting point.”

Alongside the changes that you’ve discussed so far, many people say that data journalists will eventually become regular journalists with good data literacy. What do you think of this view?

“As you say, many people have emphasised the point that data journalism is still a form of journalism, and that perhaps the ‘data’ part will become less important as data journalism practices become more widespread and more normalised. At the same time, we think it is worth considering when, why, how and for whom the distinction might matter, or not.”

Like the first Handbook, our second edition will also be translated into several languages. Watch this space in 2019, more info to follow soon!

Our next conversation

Just as our second Data Journalism Handbook asks you to reflect upon the field, we’d like to invite you to reflect on our first year of Conversations with Data.

Our first edition was released in May, and since then we’ve produced 16 distinct issues with advice on environmental reporting, scraping, fact-checking and more. As we start thinking about the new year, we want to know what you’d like to see Conversations with Data look like in 2019.

Until next time,

Madolyn from the EJC Data team

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