Using the Environment Agency’s bathing water quality data provided by DEFRA and UK Location, I’ve whipped up a very quick visualisation of my own – showing off indicators for faecal bacteria at the bathing sites.

The data source:
http://environment.data.gov.uk/doc/bathing-water.html?_view=basic&_properties=samplingPoint.lat,samplingPoint.long,latestSampleAssessment.faecalColiformCount,latestSampleAssessment.faecalStreptococciCount,latestSampleAssessment.totalColiformCount&_page=0&_sort=-latestSampleAssessment.faecalStreptococciCount

Notable parameters I used:

• view = “basic” view
• properties = lat, long, total coliform count, faecal coliform count, faecal streptococci count
• page size = 500
• sort = by faecal streptococci count (descending)

The steps to create the visualisation:

• Realised I was quite interested in seeing where the bathing sites were that contained the most faecal bacteria (Blackpool area by the looks of it)
• Tailored my own API call using instructions from the API documentation.
• Tried using Yahoo Pipes and other connecting API thingys to see what I could do within about 5-10 minutes.
• Decided to use Googles Fusion Tables as it can create maps from spreadsheet data
• The Enviroment API offers several formats, so I just changed my API call to include “.csv” intsead of “.html”.
• Then, after spending the last half year developing the LinkedGov extension for Google Refine – I immediately thought of it as the first go-to tool to shape the data and make it fit for importing into some sort of mapping API.
• I used Google Refine’s faceting & number range features to decide how to split the bacteria counts into low, medium and high.
• I exported the data from Refine as CSV to my computer.
• I uploaded the CSV into Fusion Tables – and all the hard work was done for me!
• Time taken = 15 minutes (I have experience with the Linked Data API – otherwise it would have taken me a little while longer to tailor the API call I wanted)

Please note: I have manually adjusted the banding points for the levels of bacteria so the visualisation showed a visually pleasing number of red, yellow and green markers. While a site may have a red marker – it could actually be of quite high water quality.

Total Coliform Count

Low-temperature electron micrograph of a cluster of E. coli bacteria, magnified 10,000 times. Each individual bacterium is oblong shaped. (Photo credit: Wikipedia)

Faecal Coliform Count

Faecal Streptococci Count

Gram-stained smear of streptococci (Photo credit: Wikipedia)

I found this visualisation on my server this morning – hadn’t looked around the directory structure for ages and forgot I’d made it. I think it’s quite cool, might think about carrying on with it in some way or another.

You can play with it here:

http://danpaulsmith.com/apps/postlist_new?dept=dft.

You can replace “dft” with a department acronym (e.g. co, dfe, hmrc…).

BBC have plotted the road incidents resulting in death for the last ten years in the UK.

I’m sure I’ve come across this before, but it’s a good visualisation.

Simple, meaningful and accurate.

Link: http://www.bbc.co.uk/news/uk-15975720.

Transport for London have just released a set of APIs that return various types of transport information for the city. Below is a little bar chart of London tube stations using the Passenger count API. Looking forward to using the APIs in the future!

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In Feburary I was asked to have a pop at visualising some spending data for some local UK councils. The data was in linked data format (RDF/Turtle) – so stored in a RDF store somewhere and had the Linked Data API layered on top (the Puelia implementation).

The brief was to build an open-source, interactive, cross-browser dashboard of widgets; that would allow the comparison of council’s spending data, say, per month.

After a little time spent researching, I came to the conclusion that RaphaelJS (an open-source JavaScript vector library) would fit the bill for this project nicely. The documentation wasn’t great (I’m used to that though as I’ve been using theJIT library for previous visualisation work), but understandable enough to pick some of the demos apart and get the hang of how things worked within a few days.

The great thing about RaphaelJS is that it’s simply a drawing library, so you can create a static SVG image of a banana or you can create a animated, multi-coloured, shape-shifting, real-time rotting banana, thanks to being able to manipulate and listen to events on the SVG DOM elements that form the vector image. Continue Reading →

Was just surfing around on the Information is beautiful website and came across a visualisation aimed at being a discussion starter by David McCandless on what he called “Hierarchy of visual understanding?”.

He asks whether there’s anything in his brief thoughts here and I definitely think there is – there’s also a load of visualisations that already exist based on the same flow of “data, information, knowledge, wisdom”.

I’m not sure whether I agree with the title of the post though – I think this flow is less to do with visualising information and more to do with how our brains digest information. I also half agree with the upwards arrow on the left, I think it should be a measure of increased meaning – not organisation.

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I forgot that my talk with Dave Reynolds was recorded at the Open Government Data Camp a few weeks ago. I’m at the end – about 9 minutes in!
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I didn’t actually end up using these slides on the day, but here they are with notes & links.

Please note: The geniuses behind the Linked Data API are listed here and Jeni Tennison is also the genius behind the API’s HTML Viewer, which makes API responses human friendly and a joy to develop with, transforming this into this!

More information about the “reference” data I’m using and examples of the Linked Data API & HTML Viewer can be found in the Linked Data section on the data.gov.uk website.

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“Information is the new oil” – I’ll agree with that!

David McCandless is a journalist and shares his data-detective work with TED on the visualisations he’s been creating. Really inspiring in terms of sparking the Sherlock within me and talks a lot of sense about how we may be consuming/designing information in the next few years. I’m over the moon to be in this line of work! Also ordered his book “Information is beautiful” which just arrived in the post