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October 22 2010

07:44

Manchester Police tweets and the MEN – local data journalism part 2

Manchester Evening News visualisation of Police incident tweets

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).

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.

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)

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.

October 14 2010

14:43

Manchester police tweets – live data visualisation by the MEN

Manchester police tweets - live data visualisation

Greater Manchester Police (GMP) have been experimenting today with tweeting every incident they deal with. The novelty value of the initiative has been widely reported – but local newspaper the Manchester Evening News has taken the opportunity to ask some deeper questions of the data generated by experimenting with data visualisation.

A series of bar charts – generated from Google spreadsheets and updated throughout the day – provide a valuable – and instant – insight into the sort of work that police are having to deal with.

In particular, the newspaper is testing the police’s claim that they spend a great deal of time dealing with “social work” as well as crime. At the time of writing, it certainly does take up a significant proportion – although not the “two-thirds” mentioned by GMP chief Peter Fahy. (Statistical disclaimer: the data does not yet even represent 24 hours, so is not yet going to be a useful guide. Fahy’s statistics may be more reliable).

Also visualised are the areas responsible for the most calls, the social-crime breakdown of incidents by area, and breakdowns of social incidents and serious crime incidents by type.

I’m not sure how much time they had to prepare for this, but it’s a good quick hack.

That said, I’m going to offer some advice on how the visualisation could be improved: 3D bars are never a good idea, for instance, and the divisional breakdown showing serious crime versus “social work” is difficult to visually interpret (percentages of the whole would be more easy to directly compare). The breakdowns of serious crimes and “social work”, meanwhile, should be ranked from most popular down with labelling used rather than colour.

Head of Online Content Paul Gallagher says that it’s currently a manual exercise that requires a page refresh to see updated visuals. But he thinks “the real benefit of this will come afterwards when we can also plot the data over time”. Impressively, the newspaper plans to publish the raw data and will be bringing it to tomorrow’s Hacks and Hackers Hackday in Manchester.

More broadly, the MEN is to be commended for spotting this more substantial angle to what could easily be dismissed as a gimmick by the GMP. Although that doesn’t stop me enjoying the headlines in coverage elsewhere (shown below).

Manchester police twitter headlines

September 17 2010

07:46
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