Ordnance Survey Linked Data – A Simple Spatial Query. In this blog I thought I would give an example of some very simple spatial queries using the Ordnance Survey Linked Data. When we first created the Ordnance Survey linked data not many RDF triplestores had spatial indexes, or in other words there was no easy way to say ‘find me all the Parishes in Hampshire‘ using a query based on the geometries of these regions. This functionality is fairly standard in GIS systems and a number of spatially enabled relational databases, and is now being increasingly implemented in RDF triplestores and other NoSQL technologies. To get round this issue it was decided that it would be very useful to precompute various topological relationships between the administrative areas described in the Boundary-Line(TM) linked data. What you will see in the data are explicit spatial relationships like touches, within and contains that relate the different administrative regions.
So now for some examples. Building the links… Since the launch of our improved Linked Data platform at the beginning of last month, we have seen a continued increase in the number of visits, with London the most visited area. We have been investigating who has been linking to our data and have found an app linking Boundary-Line, a range of census 2011 sources and neighbourhood information on deprivation and well-being from Open Data Communities. This application has been built by an experienced developer and involves linking many different datasets. So to help those of you who are just starting out using Linked Data, we asked our development team to create an application linking just two different data sources.
They have linked our data with Land Registry Linked Data to look up the prices paid for houses in a postcode and display the area on a map. This is a very basic application, but is an ideal start point for anyone wanting to have a go at linking data themselves. See our Land Registry case study too. Open Data Communities | Open Access to Local Data. Open Data Communities | Open Access to Local Data.