Posts Tagged ‘Ordnance Survey’

Benford’s Law and the Administrative Geography of Great Britain

July 13, 2014 Leave a comment

Just listened to the latest episode of the Infinite Monkey Cage, and was reminded of Benford’s Law. This states:

Benford’s Law, also called the First-Digit Law, refers to the frequency distribution of digits in many (but not all) real-life sources of data. In this distribution, the number 1 occurs as the leading digit about 30% of the time, while larger numbers occur in that position less frequently: 9 as the first digit less than 5% of the time. Benford’s Law also concerns the expected distribution for digits beyond the first, which approach a uniform distribution.

I was curious if that might emerge in geography (or Ordnance Survey data) somehow. Turns out if we look at the areas (in metres squared) of the polygons in the Boundary Line Product (i.e. the areas of all the counties, wards, consistuencies, districts, parishes etc. in GB) then we get a pretty good fit. In the table below the first column is the leading digit of the polygon area, the second is the percentage of areas starting with that leading digit and the third column is the value Benford’s Law predicts:

1:  30.6   30.1
2:  15.9   17.6
3:  11.3   12.5
4:  9.8     9.7
5:  8        7.9
6:  7.3     6.7
7:  6.3     5.8
8:  5.6     5.1
9:  4.9    4.6

Not bad…

Quick Play with Cayley Graph DB and Ordnance Survey Linked Data

June 29, 2014 2 comments

Earlier this month Google announced the release of the open source graph database/triplestore Cayley. This weekend I thought I would have a quick look at it, and try some simple queries using the Ordnance Survey Linked Data.

Cayley is written in Go, so first I had to download and install that. I then downloaded Cayley from here. As an initial experiment I decided to use the Boundary Line Linked Data, and you can grabbed the data as n-triples here. I only wanted a subset of this data – I didn’t need all of the triplestores storing the complex boundary geometries for my initial test so I discarded the files of the form *-geom.nt and the files of the form county.nt, dbu.nt etc. (these are the ones with the boundaries in). Finally I put the remainder of the data into one file so it was ready to load into Cayley.

It is very easy to load data into Cayley – see the getting started section part on the Cayley pages here. I decided I wanted to try the web interface so loading the data (in a file called all.nt) was a simple case of typing:

./cayley http –dbpath=./boundaryline/all.nt

Once you’ve done this point your web browser to http://localhost:64210/ and you should see something like:

Screen Shot 2014-06-29 at 10.43.35


One of the things that will first strike people used to using RDF/triplestores is that Cayley does not have a SPARQL interface, and instead uses a query language based on Gremlin. I am new to Gremlin, but seems it has already been used to explore linked data – see blog from Dan Brickley from a few years ago.

The main purpose of this blog post is to give a few simple examples of queries you can perform on the Ordnance Survey data in Cayley. If you have Cayley running then you can find the query language documented here.

At the simplest level the query language seems to be an easy way to traverse the graph by starting at a node/vertex and following incoming or outgoing links. So to find All the regions that touch Southampton it is a simple case of starting at the Southampton node, following a touches outbound link and returning the results:



Screen Shot 2014-06-29 at 10.56.15

If you want to return the names and not the IDs:


Screen Shot 2014-06-29 at 10.58.30

You can used also filter – so to just see the counties bordering Southampton:


Screen Shot 2014-06-29 at 11.01.17


The Ordnance Survey linked data also has spatial predicates ‘contains’, ‘within’ as well as ‘touches’. Analogous queries can be done with those. E.g. find me everything Southampton contains:


So after this very quick initial experiment it seems that Cayley is very good at providing an easy way of doing very quick/simple queries. One query I wanted to do was find everything in, say, Hampshire – the full transitive closure. This is very easy to do in SPARQL, but in Cayley (at first glance) you’d have to write some extra code (not exactly rocket science, but a bit of a faff compared to SPARQL). I rarely touch Javascript these days so for me personally this will never replace a triplestore with a SPARQL endpoint, but for JS developers this tool will be a great way to get started with and explore linked data/RDF. I might well brush up on my Javascript and provide more complicated examples in a later blog post…




Visualising the Location Graph – example with Gephi and Ordnance Survey linked data

March 28, 2014 2 comments

This is arguably a simpler follow up to my previous blog post, and here I want to look at visualising Ordnance Survey linked data in Gephi. Now Gephi isn’t really a GIS, but it can be used to visualise the adjacency graph where regions are represented as nodes in a graph, and links represent adjacency relationships.

The approach here will be very similar to the approach in my previous blog. The main difference is that you will need to use the Ordnance Survey SPARQL endpoint and not the DBpedia one. So this time in the Gephi semantic web importer enter the following endpoint URL:

The Ordnance Survey endpoint returns turtle by default, and Gephi does not seem to like this. I wanted to force the output as XML. I figured this could be done in the using a ‘REST parameter name’ (output) with value equal to xml. This did not seem to work, so instead I had to do a bit of a hack. In the ‘query tag…’ box you will need to change the value from ‘query’ to ‘output=xml&query’. You should see something like this in the Semantic Web Importer now:

Screen Shot 2014-03-28 at 11.28.28

Now click on the query tab. If we want to, for example, view the adjacent graph for consistuencies we can enter the following query:

prefix gephi:<>
construct {
?s gephi:label ?label .
?s gephi:lat ?lat .
?s gephi:long ?long .
?s <> ?o .}
?s a <> .
?o a <> .
?s <> ?o .
?s <> ?label .
?s <> ?lat .
?s <> ?long .

and click ‘run’. To visualise the output you will need to follow the exact same steps mentioned here (remember to recast the lat and long variables to decimal).

If we want to view adjacency of London Boroughs then we can do this with a similar query:

prefix gephi:<>
construct {
?s gephi:label ?label .
?s gephi:lat ?lat .
?s gephi:long ?long .
?s <> ?o .}
?s a <> .
?o a <> .
?s <> ?o .
?s <> ?label .
?s <> ?lat .
?s <> ?long .

When visualising you might want to change the scale parameter to 10000.0. You should see something like this:

Screen Shot 2014-03-28 at 11.40.18

So far so good. Now imagine we want to bring in some other data – recall my previous blog post here. We can use SPARQL federation to bring in data from other endpoints. Suppose we would like to make the size of the node represent the ‘IMD rank‘ of each London Borough…we can do with by bringing in data from the Open Data Communities site:

prefix gephi:<>
construct {
?s gephi:label ?label .
?s gephi:lat ?lat .
?s gephi:long ?long .
?s gephi:imd-rank ?imdrank .
?s <> ?o .}
?s a <> .
?o a <> .
?s <> ?o .
?s <> ?label .
?s <> ?lat .
?s <> ?long .
?x <> ?s .
?x <> ?imdrank . }

You will need to recast the imdrank as an integer for what follows (do this using the same approach used to recast the lat/long variables). You can now use Gephi to resize the nodes according to IMD rank. We do this using the ranking tab:

Screen Shot 2014-03-28 at 11.50.43

You should now see you London Boroughs re-sized according to their IMD rank:

Screen Shot 2014-03-28 at 11.51.51

turning the lights off and adding some labels we get:

Screen Shot 2014-03-28 at 12.04.27

Ordnance Survey Linked Data: The Search API

September 24, 2013 Leave a comment

Please note in some of the examples below I have been having trouble with wordpress ‘correcting’ quote marks in my text. If you find the queries don’t work you may need to manually replace the copied quote marks from below with new ones via your keyboard. Hope that makes sense.

One of the biggest improvements to the new Ordnance Survey Linked Data site is the much improved search functionality. You can either search over a specific dataset (e.g. the Code-Point(R) Open linked data) or over all the combined datasets. I will first give some examples of using the Boundary-Line(TM) search API.

The Boundary-Line search API explorer can be found here. The simplest use of this search API is to enter some text for the name of an administrative area or the GSS code (the ONS identifier for a statistical region) into the search box. To get started enter Southampton into the query box. You will see that the search results are returned in JSON (RSS and Atom are additional options). Results contain the URI of the entities that match your queries along with a number of useful attributes.

Note that the Request box shows the actual GET request that is being done, and you can use this GET request in your applications. Now try searching for a GSS code, enter E06000045 into the query box. You should see results for the City of Southampton returned. So far so straight forward. The search function also allows for wildcards in search, for example in the Query box type:


It is also possible to narrow search results by type. Recall that the search for Southampton returned both Westminster constituencies and a unitary authority with Southampton in their name. To just find the Westminster constituencies search for the following:

label:Southampton AND type:”

The search API also allows you to perform a number of simple spatial queries. The first of these are bounding box queries. For the Boundary-Line data you can specify a bounding box, and find all the administrative regions whose centroids lie within that bounding box. The bounding box can be expressed in eastings and northings. For example try the following:

easting:[371000 TO 374000] AND northing:[161000 TO 164500]

in the query box.

The answers can be narrowed down further by specifying the type of object that should be returned. For example to just get the civil parishes in this bounding box try the following:

easting:[371000 TO 374000] AND northing:[161000 TO 164500] AND type:”

Another type of simple spatial query we can do in the search API is ‘find me all feature of a kind type within a certain radius of a given point’. Here the point can be specified in either lat/long or easting/northing. To find all of the civil parishes in a 50 km radius of the point with easting 442339 and northing 112882 put:


into the query box and put the appropriate values in the easting and northing boxes, followed by a 50 in the radio search box. If, for example, you want to perform this query again but find civil parishes and districts enter the following into the query box:

type:” OR type:”

and try the query again.

These are just some simple examples of the search API. The full documentation is here.

Ordnance Survey Names Gazetteer – Illustrative data

September 6, 2013 Leave a comment

On behalf of my employer:

The growth and development of new, web and mobile applications demands the development of new data to enable effective location searching. In response we have published illustrative data for an updated gazetteer of names. We’d love it if you would take a look and provide us with your feedback. We want to make sure that the new product meets your needs. Access the data through OS Insight

There is also a linked data version of this data available via the above link. This contains RDF in n-triples format.

The data will be available for review until Friday 4th October 2013.

Categories: Uncategorized Tags:

Putting SPARQL on the Map with Ordnance Survey Linked Data & OS OpenSpace

August 20, 2013 Leave a comment

A colleague was asking me if I knew how to plot SPARQL query results from the Ordnance Survey linked data onto an OS OpenSpace map. Although I’d done it a few times before, it was never something I’d blogged. So here goes…

This is a lot easier than you might imagine. The first thing you want to do is perform your SPARQL query and get back the results as a csv file. I blogged about this a while back, but here is a quick recap. Let us suppose I want to plot a centroid for all the districts in England, and have their name appear in the pop up text. It is easy to perform a query to get back the easting, northing and name for all the districts. First go to the Boundary-Line(TM) SPARQL endpoint and enter the following query:

select ?x ?y ?name
?a <> ?name .
?a <> ?x .
?a <> ?y .
?a a <> .

Make sure the response format is set to CSV. Now click the query button. The “Reponse” box will have your query results, and the “Request box” should have a long complicated looking URL:

So far so easy.

Now we come to the OS OpenSpace part. It is easy to plot a text file in OS OpenSpace. To find out how go to the OS OpenSpace Code Playground and select the link “Add markers and text from a file“. You should see an example mashup showing some points plotted. To see what is going on click on “Edit in Code Playground” and you should see the javascript & HTML that produces the map. In the Javascript window you can edit the code and preview the changes. For this example the first simple thing you need to do is adjust the zoom level. To do this change:

    osMap.setCenter(new OpenSpace.MapPoint(400000, 400000), 7);


    osMap.setCenter(new OpenSpace.MapPoint(400000, 400000), 1);

so we are zoomed all the way out.

We now need to change the input text file. To do this change the following line in the sample code:

    var markersFile = “/res/mymarkers.txt”;

In this line replace /res/mymarkers.txt with the URL you got from the SPARQL endpoint in the Request box. Once you have done that click the ‘render’ button and you should now see your results plotted on an OS OpenSpace map. Click on a map pointer to display the name of the district. Easy as that.

As an exercise to the reader…consult my last few blog posts and display markers for postcodes in a district of your choosing.

Ordnance Survey SPARQL Endpoint

August 7, 2013 Leave a comment

I just wanted to quick mention one feature of the Ordnance Survey linked data SPARQL endpoints that I think it pretty neat.  Go to the SPARQL endpoint and try one of the queries from my last four blogs posts. In this post I’ll got with the following simple query (recall this query gets the name, lat, long, gss code and unit_id for all districts in Great Britain):

select ?name ?lat ?long ?gss ?unit_id



?x <> ?name .

?x <> ?lat .

?x <> ?long .

?x <> ?gss .

?x <> ?unit_id .

?x a <> .


You will notice that on hitting the query button that a box will appear that says “Request” and a rather long URL will appear:


You can now use this URL to issue a GET request in PHP, Javascript etc. and use these output within a web application just as you would with any API call. To see this working in a simple way copy the long URL you get from your SPARQL query and at the command line (if running something UNIXy) type:


where LONG_URL is your long URL. You should now see the JSON response from that GET request.

Happy SPARQLing…


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