Home > linked data, Semantic Web > Adventures with Kasabi…and a request for help…

Adventures with Kasabi…and a request for help…

I’ve been playing around with Kasabi a bit of late. Kasabi is a new information market place from Talis that provides a useful place to publish your data, and then build services on top of it.

By way of a quick example you’ll see that the currently Ordnance Survey Linked Data is hosted in Kasabi here. There are a number of standard APIs provided with each dataset such as a SPARQL endpoint, search API etc. Kasabi provides an easy way to map complex SPARQL queries to simple API queries. For example, this API provides an easy way to do topological queries on the Ordnance Survey Linked Data. For example:


will find all regions that touch The City of Southampton.

This API gives you a list of all postcodes (and their lat/long) within a particular region. For example:


will find all postcodes inThe City of Southampton. Additionally we can apply a style sheet to get back the same information as KML:


Kasabi also provides a handy place to store and host data, and one Sunday afternoon I decided to see how easy it would be to create a couple of hyperlocal datasets: one for Southampton and one for Hampshire. The basic approach in creating these hyperlocal datasets was to effectively ‘cookie cut’ region specific data from a number of different linked (open) data sets and put them into one store. So for Southampton and Hampshire we have a list of: airports, bus stops, stations, schools, GPs, hospitals, renewable energy generators, heritage sites, councillors, crime statistics, administrative regions and postcodes…   Each important element, like schools or hospitals, is linked to a postcode, district, ward—and in the case of Hampshire—county. The Ordnance Survey linked data is effectively acting as the clue between disparate sources of information. The fact that each of these datasets was provided as linked data, and furthermore referenced common identifiers for administrative regions and postcodes, meant it was very easy to bring them together in one store. Some sample queries are provided here. It gets more interesting when you combine elements from different datasets to, for example, ask questions like ‘find me GPs in my ward, and all the bus stops within a 100 metre radius of those GPs’.  If one were extra paranoid it would then be possible to extend the query to only find bus stops in areas of low anti-social crime levels. These queries are all well and good, or ‘nerdy, but nice’ as Andrew Stott put it.

What I was really hoping to do was build a nice webapp on top of this integrated data. Anyone who has seen my previous mash-ups will know that web design is not amongst my key skills, so Zach Beauvais suggested I put word out to the developer community to see if anyone fancied building on this data to make something cool and interesting like (for example) the (in)famous postcode paper. Any volunteers? :)




About these ads
  1. No comments yet.
  1. February 21, 2012 at 4:36 pm

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s


Get every new post delivered to your Inbox.

Join 2,189 other followers

%d bloggers like this: