Using the British Punk Rock Band Sideburns' 1977 chart as a guide, Simon Rogers asks, 'do you need to be part of a major news operation or work for a big media company to be a data journalist, or can anyone do it?'
This is a chord… this is another… this is a third. NOW FORM A BAND
So went the first issue of British punk fanzine Sideburns in 1977 in the “first and last part in a series”.
It might be 35 years old, but this will do nicely as a theory of data journalism in 2012.
Why? Arguably punk was most important in its influence, encouraging kids in the suburbs to take up instruments, with little or no musical training. It represented a DIY ethos and a shake-up of the old established order. It was a change.
Crucial to it was the idea: anyone can do it.
Is the same true of data journalism? Do you need to be part of a major news operation, working for a big media company to be a data journalist?
Now is the time to examine this – in May 2010, we published this piece on how reporters would soon be flooded with a “tsunami of data”. Two years on and data journalism is part of the fabric of what we, and many other news organisations do. There are even different streams now – short-form, quick-and-dirty data visualisations of the kind we do every day on the Datablog, right through to complex investigations and visualisations – such as our riots data analysis or the kind of projects which made the shortlist of the Data Journalism Awards, from around the world.
So, can we still say that anyone can do data journalism; in the first and last part in a series. Would this work?
NOW BE A DATA JOURNALIST
OK, it lacks a certain 1976 grittiness, but the theory is there. You don’t have to be a developer or a coder to be a data journalist.
We asked our Twitter followers what they thought (and you can see a storify of the discussion below). A couple stand out to me:
Maybe everyone can do it, but not everyone can do it well. Like so many other things, done well is a mix of art and science
Mutual disregard for shared constructs of authority? Shared overarching aim of revealing reality away from the facade?
But is that enough? The thing about data journalism is that there are so very many ‘chords’ – just the free ones could fill several training manuals: Google fusion tables, Tableau, Gephi, OutWit Hub, Google Refine… Can anyone really do it?
He says there are some parallels – with a crucial difference.
While I agree with the premise – it’s never been easier to do this stuff than it is right now – I think there are a few steps beyond just learning three chords when doing data journalism. For one, Legs [McNeil, who coined the word ‘punk’] didn’t really say a band needed to be *good* but I’d like to think we’d require that for data journalism
The theory goes that the punk bands we remember best are the ones that were good – but there needed to be a whole lot of kids experimenting and sounding awful before they got there.
For what it’s worth, I like the fact that there are many just trying stuff out, even if it is forgettable – because some of it will be amazing.
In fact, data journalism is a great leveller. Many media groups are starting with as much prior knowledge and expertise as someone hacking away from their bedroom. Many have, until very recently, no idea where to start and great groups of journalists are still nervous of the spreadsheets they are increasingly confronted with.
It’s rare for the news site reader to find themselves as powerful as the news site editor, but that’s where we are right now – and that power is only increasing as journalists come to rely more and more on their communities for engagement and stories.
Where I think there are more parallels are in the fact that this is a young community (in years if not always age), and one that’s actively teaching itself new tricks every day. That same vitality and excitement that motivated punk, it’s motivating news hackers right now
Meanwhile, more and more news teams are discovering that data equals stories and bulking up their teams. Some would say it’s just an extension of work they’ve always done, but that’s to ignore the huge shift in power the web has created.
“Some people think that this stuff is instant,” says Sinker. “Even though there are incredible tools now, there is still a learning curve.” Out there in the world, there are lots of people who have just formed a band and got on with it – despite the obstacles.
When the team started, it was sparse, to say the least, says Florencia Coelho.
We had no web programmer or CAR [computer assisted reporting] people in our newsroom. We gathered an interactive designer and we self taught Tableau with their free training videos in what we called our Tableau days, in a Starbucks at a shopping mall in Buenos Aires.
The team is still not exactly huge – but it is easily the best data journalism site in South America and one of the most innovative around. You can read more about it on NiemanLab.
It’s not all about investigative reporting. First, all reporting probably counts as investigative journalism, but if you want to play semantics, then I will see your “investigative” and raise you “analytical”. Not all data journalism has to bring down the government – it’s often enough for it to shine a light in corners that are less understood, to help us see the world a little clearer. And if that’s not investigative, what is?
There’s a great democratisation of data going on. Rather than the numbers belonging to the experts, they belong to all of us – and data journalism is part of that reclaiming of the facts. Even at the OECD, users’ voices are part of the process, making up the core analysis that lies at the heart of the Better Life Index on wellbeing.
And, just to be clear – data journalism doesn’t have to mean data visualisation. It is not about producing charts or intricate graphics – the results of data journalism just happen to lend themselves to that. Sometimes a story is best told in images and infographics, other times it works as words and stories. It’s the ultimate in flexible formats.
But, when it comes to visualisations, what really comes across from this analysis of Visual.lys most viral infographics is how sometimes the simplest things can flood the web.
Single charts are likely successful because they are easy to consume; the viewer only needs to learn how to read one “chunk” of visualization to get the whole story. Simplicity lends itself to quick understanding and sharing, whereas complexity can prevent a viewer from reaching those points. Curiously, mixed charts, which is what we commonly think of as the typical form of an infographic, is the least successful here, perhaps because they take more mental work to consume completely, again pointing to simplicity and brevity as strengths in visual communication.
As the post points out, however, sometimes things done messily can still be hits – it’s the information that’s vital. People are willing to forgive a lack of perfection; they are much less forgiving for those who get the facts wrong.
Data visualisation experts will always say: allow the data to choose the visualisation, that it’s crucial for the visualisation to fit the numbers – and not the other way around. That question equally applies itself to whether something needs a visualisation in the first place.
Of course, for some people, this will never be journalism. But then, who cares? While they’re worrying about the definitions, the rest of us can just get on with it.
Punk eventually turned into new wave, new wave into everyday pop and bands that just aren’t as exciting. But what it did do is change the climate and the daily weather. Data journalism is doing that too.
In the words of Joe Strummer:
People can do anything
World government data