Last week Steve Peters announced his excellent visualisation app for the English Indices of Multiple Deprivation (Steve’s blog post and the visualisation itself).

It allows you to explore the deprivation rankings in various domains (overall, crime, health, education etc), highlighting the most and least deprived areas in the country. The deprivation data is pulled live via SPARQL queries from the Open Data Communities site that Swirrl set up.

The app combines this with various other APIs (OpenlyLocal, TheyWorkForYou, MapIt amongst others) to pull in related information, such as ward and local authority boundaries, councillors and MPs representing each area, and schools.

Overall the app is one of the nicest web-based apps I’ve seen for exploring and visualising data. A couple of points about it are particularly worth noting.

The creator of this is an ‘amateur’ programmer who did it in his spare time in a few weeks. It shows how open data, especially linked open data, enables powerful data integration and exploration tools to be built at low cost. This didn’t require buying expensive packaged software or hiring a team of consultants. Open data with good APIs can greatly reduce the costs of data search and data integration for the public sector.

The app works purely via Javascript in the browser and pulls its data from public APIs. It doesn’t involve any special server-side code. Visualisations like this can easily be embedded into an existing web page or blog. It demonstrates how easily value-added views of data can be distributed via the web, helping to get the information to people that need it.

What makes this possible is the existence of several open APIs that share enough identifiers in common to allow effective linking between them. These don’t need to be Linked Data in the ‘formal’ TBL sense, but Linked Data is designed to address exactly this problem and more sources of useful Linked Data would make building things like this even easier.

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