In 2007 Bill Kovach and Tom Rosenstiel published The Elements of Journalism. With the concept of ‘journalism’ increasingly challenged by the fact that anyone could now publish to mass audiences, their principles represented a welcome platform-neutral attempt to articulate exactly how journalism could be untangled from the vehicles that carried it and the audiences it commanded.
In this extract from a forthcoming book chapter* I attempt to use Kovach and Rosenstiel’s principles (outlined in part 1 here) as the basis for a set that might form a basis for (modern) data journalism as it enters its second and third decades.
Principle 1: Data journalists should strive to interrogate data as a power in its own right
When data journalist Jean-Marc Manach set out to find out how many people had died while migrating to Europe he discovered that no EU member state held any data on migrants’ deaths. As one public official put it, dead migrants “aren’t migrating anymore, so why care?”
Similarly, when the BBC sent Freedom of Information requests to mental health trusts about their use of face-down restraint, six replied saying they could not say how often any form of restraint was used — despite being statutorily obliged to “document and review every episode of physical restraint which should include a detailed account of the restraint” under the Mental Health Act 1983.
The collection of data, the definitions used, and the ways that data informs decision making, are all exercises of power in their own right. The availability, accuracy and employment should all be particular focuses for data journalism as we see the expansion of smart cities and wearable technology. Continue reading →
In this second extract from a forthcoming book chapter I look at the role that computational thinking is likely to play in the next wave of data journalism — and the need to problematise that. You can read the first part of this series here.
Computational thinking is the process of logical problem solving that allows us to break down challenges into manageable chunks. It is ‘computational’ not only because it is logical in the same way that a computer is, but also because this allows us to turn to computer power to solve it.
“To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability. Just as the printing press facilitated the spread of the three Rs, what is appropriately incestuous about this vision is that computing and computers facilitate the spread of computational thinking.”
This process is at the heart of a data journalist’s work: it is what allows the data journalist to solve the problems that make up so much of modern journalism, and to be able to do so with the speed and accuracy that news processes demand. Continue reading →
In the first of three expanded extracts from a forthcoming book chapter on ‘The next wave of data journalism’ I outline some of the ways that data journalism is reinventing itself, and adapting for a world which is rapidly changing again. Where networked communications and processing power were key in the 2000s, automation and AI are becoming key in the decade to come. And just as data journalism raised the bar for journalism as a whole, the bar is about to be raised for data journalism itself.
Data journalism isn’t doing enough. Now into its second decade, the noughties-era technologies that it was built on – networked access to information and vastly improving visualisation capabilities – are now taken for granted, just as the ‘computer assisted’ part of its antecedent Computer Assisted Reporting was.
In just ten years data journalism has settled down into familiar practices and genres, from the interactive map and giant infographics to the quick turnaround “Who comes bottom in the latest dataset” write-up. It’s a sure sign of maturity when press officers are sending you data journalism-based media releases.
Now we need to move forward. And the good news is: there are plenty of places to go. Continue reading →