Ask data journalists and most will tell you that data is just another source for a reporter's story. But it is so much more than that.
But has it always been this way? 10 years ago, one of the most authoritative books on the subject was published, the Data Journalism Handbook, edited by Jonathan Gray and Liliana Bounegru, now both lecturers at the Department of Digital Humanities, King’s College London.
A decade on, the editors published a new edition which is open access on Amsterdam University Press. It has 54 chapters from 74 leading researchers and practitioners of data journalism, including the likes of Al Jazeera, BBC, Der Spiegel and the Washington Post.
They give a 'behind the scenes' look at datasets, data infrastructures, and data stories in newsrooms, startups, civil society organisations and beyond.
Journalism.co.uk caught up with Gray and Bounegru to discuss how much has changed in the field of data journalism over the past decade.
How has the prominence of data journalism and data-led investigations changed in the past 10 years?
Liliana Bounegru: You can trace back many histories of data journalism and its various techniques and communities around the world. But the label "data journalism" is more recent and has been steadily gaining traction over the past decade – from the rise of data journalism roles and data reporting teams to dedicated awards, events and training activities.
Courtesy of Liliana Bounegru (above) lecturer in digital methods, Department of Digital Humanities, King’s College London
Over the past few years, the field has been gaining much more widespread recognition, not just as a form of novelty or innovation, but as an important element of reporting on societal issues in which large data sources or computational methods are somehow involved – for example in the case of "big leaks" (such as Wikileaks and Panama Papers) or reporting on platforms, algorithms, misinformation and ad-tech.
How can journalists create their own data? What were the barriers ten years ago and do they still remain?
Jonathan Gray: We have seen that journalists can assemble their own data – from documenting knife crime, land conflicts, worker deaths or air pollution to gathering data from the web and social media platforms.
Courtesy of Jonathan Gray (above), senior lecturer in critical infrastructure studies, Department of Digital Humanities, King's College London
Some of these data-gathering approaches have been available for decades. For example, the Spotlight film prominently highlighted how the Boston Globe used spreadsheets in the early 2000s as part of their investigative reporting into child abuse cover-ups. Now we also have networked spreadsheets, open-source sensing devices, web scraping and many other techniques of gathering data.
But despite these developments, gathering data can still be time consuming and challenging. It requires not only technical know-how but also learning how to assemble and work with diverse materials, communities and infrastructures.
How much has changed in respect to the subject or focus of data-led reporting?
LB: While many earlier data journalism projects used statistical or institutional data, recently there has been a lot more experimentation with data from the web, social media and other digital infrastructures and devices.
Algorithmic accountability reporting is a beat that is emerging in some newsrooms to critically scrutinise algorithms and data infrastructures, and hold them to account. Here there are significant opportunities for collaborations between journalists, civil society groups and researchers.
What other significant changes in data journalism have you seen?
JG: There has been a shift away from an earlier optimism about looking at the "numbers behind the news", "facts" behind headlines and opportunities of deploying computational techniques. Now, we see critical engagement and sober assessment of the partiality and limits of data and how computational technologies are not just expert tools but also increasingly implicated in everyday life, sometimes (though not always) in troubling ways.
One of the challenges for critical data practice is how data journalism projects can tell stories both with and about data including the various actors, processes, institutions, infrastructures and forms of knowledge through which data is made.
There have been some really interesting examples of this since the book was published, such as investigations into the making of carbon emissions data and stories about the making of air pollution data. If any readers have other good examples of telling stories about the making of data we would love to hear them.
What does the future hold for data journalism?
LB: Here are three things we hope to see more of.
Firstly, data journalists critically engaging with data as well as using it. This includes journalists not just working within dominant data regimes but also making space to investigate, interrogate, intervene around, and democratically reshape data infrastructures that shape collective life.
Secondly, more data journalism projects undertaken with the involvement of marginalised communities on issues which they are affected by. There are lots of community-based and inclusive data reporting out there and we hope that these approaches continue to flourish.
Thirdly, more reflexive ways of telling in data journalism. That means developing forms of storytelling that emphasise how data is always situated, partial and accompanied by a degree of uncertainty, as well as exploring more inventive and inclusive formats for making data relatable.
JG: As we mention in the introduction of the book, data can be viewed not just in terms of factual representations, but also in terms of living relations. We hope that some of the chapters inspire other ways of thinking about how data journalism may play a role in critically engaging with the world around us, and sparking curiosity and imagination around how else we might live together.
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