Interactive Infographics: A New View of Statistics Visualization

12 March 2013
By Vladimir Timashov, Project Manager

DataArt data visualization competence centre announces completion of a prototype which allows visualizing councils’ spending in England regions and counties. Built using HTML5, Raphael, and D3.js, the application contains interactive visualizations available on all major browsers and platforms, including the Apple iPad. Also, using these technics we could visualize statistics from any independent source and form the appearance of each infographic according to the data.

We’ve used data collected by Openlylocal, a great project which gathers and organizes Local Government information. As a result, you can compare on the chart regional spending on culture between Yorkshire and East Anglia, the financial situation of the North and South, or the budgets of Somerset and Gloucestershire Counties. Unfortunately the data set we used is not complete, so our visualization contains gaps and blind spots on the map.

Visualization with a map of England shown. The user may filter by regions as well as categories.

We’ve decided to show spending as a circular bar. Each of the bars represents the spending in a particular region. At the same time the circles are split into several arcs showing spending in a particular category. We’ve used colour coding to compare expenses in the regions: darker colours mean more costs.

The visualization is interactive: one can select a region on the map to show a detailed breakdown of the costs in that region. Filter by region and a category of costs is also available.
Regarding technology, we used HTML5 to develop this prototype. Therefore the model is available on all the latest versions of popular browsers like Chrome, Firefox, Internet Explorer, as well as mobile platforms (including Apple iPad).

The application is the perfect instrument to visualize constantly changing data: the server immediately collects and updates information and Raphael and D3 present it in a colourful, readable, and easy-to-understand form.

We are looking forward to developing more visualization sets to show the real art of the data. Follow our news on DataArt blog!

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