A week ago I blogged about how the Manchester Evening News were using data visualisation to provide a deeper analysis of the local police force’s experiment in tweeting incidents for 24 hours. In that post Head of Online Content Paul Gallagher said he thought the real benefit would “come afterwards when we can also plot the data over time”.
Now that data has been plotted, and you can see the results here.
In addition, you can filter the results by area, type (crime or ‘social work’) and category (specific sort of crime or social issue). To give the technical background: Carl Johnstone put the data into a mysql database, wrote some code in Perl for the filters and used a Flash applet for the graphs.
It’s a good follow up, although at the current time somewhat short of illuminating findings. The page introducing the interactive chart links to just one time-based story from the data: that between 9pm and 10pm at night a quarter of all calls relate to anti-social behaviour. There’s no indication that journalists will be digging for others (UPDATE: Paul has since told me they used the data to produce “separate stories for each of our district weekly print titles”.
The text also fails to invite users to contribute their own insights, instead presenting the tools as a way to find a personalised ‘story’ rather than the start of any collaborative process.
The visualisation tool could also be improved. While allowing you to look at any particular category and area in isolation, it doesn’t allow you to visually compare them to see, for example, whether Bolton or Bury is quieter at night, or whether burglary peaks in the morning in one area, but in the evening in another.
And of course, they’ve not linked to the original data to allow a helpful developer to do that for them (going into greater depth: the URL for each set of results is ‘hackable’ – i.e. easy to construct if you know what you’re looking for – and so easier to scrape the resulting tweets. However, the chart itself with the numbers in it is Flash-based which creates a problem). UPDATE: Paul tells me they are planning to make the data public and invite developers to do their own work, but the eruption of other major news in the city means they “just have not had time yet”.
On the positive side, it’s good to see a clear basic visualisation with a base starting at 0.
If you do want the raw data, it’s been put together by The Guardian’s Michael Brunton-Spall and is available here.
This formed the basis for a day of activity at a Hacks & Hackers Day last week, which the Manchester Evening News took part in. The results of that can be read on the Scraperwiki blog and on Andy Dickinson’s blog. These included:
“David Kendal produced his own project mapping 999 calls in the area. He took the tweet data and put it through the Yahoo placemaker tool, plotting information on a Google map, to see which areas got calls over certain periods of time.
“Yuwei Lin and Enrico Zini [produced] a GMP tweet database, and showed a very neat search tool that allowed analysis of certain aspects of the police data (3257 items).”
And unrelated to the police tweets but of enormous use to journalists was the creation of judgmental.org.uk, a website of United Kingdom case judgment data.
“At the moment this is only available via Bailli and the team wanted to make something more usable and searchable (Bailli’s data cannot be scraped or indexed by Google).
“It is still a work in progress, but could eventually provide a very useful tool for journalists. Although the data is not updated past a certain point, journalists would be able to analyse the information for different factors: which judges made which judgments? What is the level of activity in different courts? Which times of year are busier? It could be scrutinised to determine different aspects of the cases.”
I’m immensely pleased to see this come about as a result in part (I’m told) of an investigation on Help Me Investigate last year.