Over the weekend Fleet Street Blues has had a bee in its bonnet about the “pretence” of data journalism and Saturday’s Guardian front page: “Half UK’s young black men out of work“.
This, says FSB, is a lie that demonstrates the “pretence” that “‘crunching the numbers’ is somehow an an abstract, scientific, mathematical task”. Continue reading
There’s a persuasive argument being made by Francis Irving and Rufus Pollock in a joint blog post about the growth of data management systems – the ‘DMS’ to content management systems’ ‘CMS’:
“Just as then we wrote HTML in text files by hand and uploaded it by FTP, now we analyse data on our laptops using Excel, and share it with friends by emailing CSV files.
“But it reaches the point where using the filesystem and Outlook as your DMS stretches to breaking point. You’ll need a proper one.
“Nobody really knows what a proper one will look like yet. We’re all working on it.”
Their post lists what a DMS needs to do and the companies already trying to solve the ‘DMS problem’ from different directions: a list which includes Google Docs (“coming from the web spreadsheet direction”), the data social network BuzzData, visualisation tool Tableau, data marketplaces, operating systems, Scraperwiki, and PANDA (“making a DMS for newsrooms”)
It’s a well-drawn picture from an angle which I haven’t seen before. Certainly, a number of news organisations are trying to reduce the friction of producing content for different platforms by ‘atomising’ it in data-driven production processes (where a piece of content might be assembled and presented differently depending on the platform it is accessed through, for example), and their internal systems can probably be added to the list above.
What do you think? Is this a problem that’s being addressed in your own organisation?
Here are the latest answers to some questions – this time relating to these predictions for 2012:
The main advantages are that it’s very sticky – users tend to leave streams on in the same way that they leave 24 hour news channels on, or keep checking back to Facebook and Twitter (which have helped popularise the ‘stream’ interface).
If you compare that to the traditional story layout format, where users scan across the page but then leave the site if there’s nothing obviously of interest, you can see the difference.
I think there’s room for both, but if you want to know what’s new since the last time you looked, the stream works very well. And it’s not difficult to combine that with subject or region pages that show the most important news of that day, for example.
I think it can work for every kind of news: the stream says ‘Here’s what’s new’ across all topics; the ‘layout’ says ‘Here’s what we think is important’ – in other words, it performs a more traditional ‘snapshot’ function akin to the daily newspaper layout.
The basic skills are the same as any journalist: a nose for a story, and the ability to communicate that clearly. In data journalism terms that means being able to interrogate data quickly and then focus on the most important facts within it.
That will most likely involve being able to use spreadsheet formulae to work out, for example, the proportion of time or money being spent on something, or to combine different datasets to gain new insights or overcome obstacles put in your way by those publishing the data.
You also need to be able to avoid mistakes by cleaning data, for example (often the same person or organisation will be named differently, for example), and by understanding the context of the data (for example, population size, or methodology used to gather it).
Finally, as I say, you need to be able to communicate the results clearly, which often means pulling back from the data and not trying to use it all in your telling of the story (just as you wouldn’t use every quote you got from a source) but keeping it simple.
The following 3 videos first appeared on the Help Me Investigate blog, Help Me Investigate: Health and Help Me Investigate: Welfare. I thought I’d collect them together here too. As always, these are published under a Creative Commons licence, so you are welcome to re-use, edit and combine with other video, with attribution (and a link!).
First, Heather Brooke’s tips for starting to investigate public bodies:
Her advice on investigating health, welfare and crime:
And on using the Data Protection Act:
In almost a decade of teaching online journalism I repeatedly come up against the same two problems:
Until now I’ve addressed these problems largely through teaching and individual feedback. But for the next 3 months I’ll be trying a new way of organising students that hopes to address those two problems. As always, I thought I’d share it here to see what you think.
Here’s what I’m trying (for context: this is on an undergraduate module at Birmingham City University):
Students are allocated one of 5 roles within a group, investigating a particular public interest question. They investigate that for 6 weeks, at which point they are rotated to a different role and a new investigation (I’m weighing up whether to have some sort of job interview at that point).
The group format allows – I hope – for something interesting to happen: students are not under pressure to deliver ‘stories’, but instead blog about their investigation, as explained below. They are still learning newsgathering techniques, and production techniques, but the team structure makes these explicitly different to those that they would learn elsewhere.
The hope is that it will be much more difficult for them to just transfer print-style stories online, or to reach for he-said/she-said sources to fill the space between ads. With only one story to focus on, students should be forced to engage more, to do deeper and deeper into an issue, and to be more creative in how they communicate what they find out.
(It’s interesting to note that at least one news organisation is attempting something similar with a restructuring late last year)
Only one member of the team is primarily concerned with the story, and that is the editor:
It is the editor’s role to identify what exactly the story is that the team is pursuing, and plan how the resources of the team should be best employed in pursuing that. It will help if they form the story as a hypothesis to be tested by the team gathering evidence – following Mark Lee Hunter’s story based inquiry method (PDF).
Qualities needed and developed by the editor include:
The community manager’s focus is on the communities affected by the story being pursued. They should be engaging regularly with those communities – contributing to forums, having conversations with members on Twitter; following updates on Facebook; attending real world events; commenting on blogs or photo/video sharing sites, and so on.
They are the two-way channel between that community and the news team: feeding leads from the community to the editor, and taking a lead from the editor in finding contacts from the community (experts, case studies, witnesses).
Qualities needed and developed by the community manager include:
6 steps to get started in community management can be found in this follow-up post.
While the community manager is focused on people, the data journalist is focused on documentation: datasets, reports, documents, regulations, and anything that frames the story being pursued.
It is their role to find that documentation – and to make sense of it. This is a key role because stories often come from signs being ignored (data) or regulations being ignored (documents).
Qualities needed and developed by the data journalist include:
Here’s a step by step on how to get started as a data journalist.
The multimedia journalist is focused on the sights, sounds and people that bring a story to life. In an investigation, these will typically be the ‘victims’ and the ‘targets’.
They will film interviews with case studies; organise podcasts where various parties play the story out; collect galleries of images to illustrate the reality behind the words.
They will work closely with the CM as their roles can overlap, especially when accessing sources. The difference is that the CM is concerned with a larger quantity of interactions and information; the MM is concerned with quality: much fewer interactions and richer detail.
Qualities needed and developed by the MMJ include:
(This was called Network Aggregator in an earlier version of this post) The CJ is the person who keeps the site ticking over while the rest of the team is working on the bigger story.
They publish regular links to related stories around the country. They are also the person who provides the wider context of that story: what else is happening in that field or around that issue; are similar issues arising in other places around the country. Typical content includes backgrounders, explainers, and updates from around the world.
This is the least demanding of the roles, so they should also be available to support other members of the team when required, following up minor leads on related stories. They should not be ‘just linking’, but getting original stories too, particularly by ‘joining the dots’ on information coming in.
Qualities needed and developed by the CJ include:
And here’s a post on ‘How to be a network journalist‘.
Examples of network aggregation in action:
If this works, I’m hoping students will produce different types of content on their way to that ‘big story’, as follows:
You can read more on the expectations of each role in this document. And there’s a diagram indicating how group members might interact below:
Investigations team flowchart
What will make the difference is how disciplined the editor is in ensuring that their team keeps moving towards the ultimate aim, and that they can combine the different parts into a significant whole.
UPDATE: A commenter has asked about the end result. Here’s how it’s explained to students:
“At an identified point, the Editor will need to organise his or her team to bring those ingredients into that bigger story – and it may be told in different ways, for example:
- A longform text narrative with links to the source material and embedded multimedia
- An edited multimedia package with links to source material in the accompanying description
- A map made with Google Maps, Fusion Tables or another tool, where pins include images or video, and links to each story”
If you’ve any suggestions or experiences on how this might work better, I’d very much welcome them.
Wonderful post by Tony Hirst in which he sort-of-coins* a lovely neologism in explaining how data can be “laundered”:
“The Deloitte report was used as evidence by Facebook to demonstrate a particular economic benefit made possible by Facebook’s activities. The consultancy firm’s caveats were ignored, (including the fact that the data may in part at least have come from Facebook itself), in reporting this claim.
“So: this is data laundering, right? We have some dodgy evidence, about which we’re biased, so we give it to an “independent” consultant who re-reports it, albeit with caveats, that we can then report, minus the caveats. Lovely, clean evidence. Our lobbyists can then go to a lazy policy researcher and take this scrubbed evidence, referencing it as finding in the Deloitte report, so that it can make its way into a policy briefing.”
So, perhaps we can now say “Follow the data” in the same way that we “Follow the money”?
*Although a search for “money laundering” generates thousands of results on Google, most of them seemingly influenced by serial neologist William Gibson‘s use of the term to refer to using illegally acquired data, I can’t find an example of it being used in the way that Tony means it.
UPDATE [Feb 14 2012]: Full Fact picked up the challenge and dug into the data:
“The crucial difference is in methodology – while the TPA used individuals as its basis, the IFS used households as provided by the Government data.
“This led to substantially different conclusions. The IFS note that using household income as a measure demonstrates increased gains for households with two or more earners. As they state:
“”families with two taxpayers would gain more than families with one taxpayer, who tend to be worse off. Thus, overall, better-off families (although not the very richest) would tend to gain most in cash terms from this reform…””
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Here’s a great test for eagle-eyed journalists, tweeted by Guardian’s James Ball. It’s a tale of two charts that claim to show the impact of a change in the income tax threshold to £10,000. Here’s the first:
And here’s the second:
So: same change, very different stories. In one story (Institute for Fiscal Studies) it is the the wealthiest that appear to benefit the most; but in the other (Taxpayers’ Alliance via Guido Fawkes) it’s the poorest who are benefiting.
Did you spot the difference? The different y axis is a slight clue – the first chart covers a wider range of change – but it’s the legend that gives the biggest hint: one is measuring change as a percentage of gross income (before, well, taxes); the other as a change in net income (after tax).
James’s colleague Mary Hamilton put it like this: “4.5% of very little is of course much less than 1% of loads.” Or, more specifically: 4.6% of £10,853 (the second decile mentioned in Fawkes’ post) is £499.24; 1.1% of £47,000 (the 9th decile according to the same ONS figures) is £517. (Without raw data, it’s hard to judge what figures are being used – if you include earnings over that £47k marker then it changes things, for example, and there’s no link to the net earnings).
In a nutshell, like James, I’m not entirely sure why they differ so strikingly. So, further statistical analysis welcome.
UPDATE: Seems a bit of a Twitter fight erupted between Guido Fawkes and James Ball over the source of the IFS data. James links to this pre-election document containing the chart and this one on ‘Budget 2011’. Guido says the chart’s “projections were based on policy forecasts that didn’t pan out”. I’ve not had the chance to properly scrutinise the claims of either James or Guido. I’ve also yet to see a direct link to the Taxpayers’ Alliance data, so that is equally in need of unpicking.
In this post, however, my point isn’t to do with the specific issue (or who is ‘right’) but rather how it can be presented in different ways, and the importance of having access to the raw data to ‘unspin’ it.
The Scotsman has a newish data blog, set up (I’m rather proud to say) by one of my former PA/Telegraph trainees: Jennifer O’Mahony. This is particularly important as so much data covered in the ‘national’ press tends to be English-only due to devolution.
The Department of Education, for example, only publishes English education data. If you want Scottish education data you need to go to the Scottish Government website or Education Scotland. Ofsted inspects schools in England; for Scottish schools reports you need to visit HM Inspectorate of Education. (Meanwhile, the National Statistics site, publishes data from England, Scotland, Wales and Northern Ireland).
So if there’s any Scottish data – or that of Wales or Northern Ireland – that you want me to help with, let me or Jennifer know. By way of illustrating the process, here’s a post over on Help Me Investigate: Education on how I helped Jennifer collect data on free school meals in Scotland.
On the same note of non-national data journalism, here’s a particularly nice bit of data visualisation at the Liverpool Post. It’s not often you see treemaps on a local newspaper website – this one was designed by Ilan Sheady based on data gathered by City Editor David Bartlett after a day’s data journalism training.
One of the easiest ways to get someone started on data visualisation is to introduce them to word clouds (it also demonstrates neatly how not all data is numerical).
Using tools like Wordle and Tagxedo, you can paste in a major speech and see it visualised within a minute or so.
But is a word cloud the best way of visualising speeches? The New York Times appear to think otherwise. Their visualisation (above) comparing President Obama’s State of the Union address and speeches by Republican presidential candidates chooses to use something far less fashionable: the bar chart.
Why did they choose a bar chart? The key is the purpose of the chart: comparison. If your objective is to capture the spirit of a speech, or its key themes, then a word cloud can still work well, if you clean the data (see this interactive example that appeared on the New York Times in 2009).
But if you want to compare it to speeches of others – and particularly if you want to compare on specific issues such as employment or tax – then bar charts are a better choice. Compare, for example, ReadWriteWeb’s comparison of inaugural speeches, and how effective that is compared to the bar charts.
In short, don’t always reach for the obvious chart type – and be clear what you’re trying to communicate.
UPDATE: More criticism of word clouds by New York Times software architect here (via Harriet Bailey)
Obama inaugural speech word cloud by ReadWriteWeb
Yesterday saw the launch of the first (surprisingly) international data journalism awards, backed by the European Journalism Centre*, Google, and the Global Editors Network.
There are 6 awards – 3 categories, each split into national/international and local/regional subcategories: investigative journalism; visualisation; and apps.
Each comes with prize money of 7,500 euros.
The closing date for entries is April 10. It’s particularly good to see a jury and pre-jury that isn’t dominated by Anglo-American traditional media, so if your work is unconventionally innovative it stands a decent chance of making it through. There’s also no specification on where your work is published, so students and independent journalists can enter.
The one thing I’d like to see in future years is the ‘visualisation and storytelling’ category expanded to include non-visual storytelling – there’s a tendency to reach for visualisation as a way to communicate data when other methods could be just as, or more, engaging.
*Declaration of interest: I am on the editorial board for the EJC’s Data Driven Journalism project.
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