Guest Blog: Ordnance Survey Maps Providing Visual Representation of Data

OS1Ordnance Survey (OS) has over 225 years’ experience in creating beautiful maps. First commissioned in the late 18th century to protect the nation from the threat of Napoleonic invasion. Our accurate and beautiful mapping is used to visualise data in order to better imagine solutions to problems and also as a source of data itself.

Below are some of our favourite examples.

OS Data can be used to provide a simple visual and contextual backdrop for many other data sources. The image below depicts the extent of the flooding in the Somerset Levels in January 2014. Here backdrop and height data has been combined with Environment Agency flood data.


In the first instance, OS was a military operation which has given rise to strong links with the Civil Contingencies Secretariat within Cabinet Office. As part of the team involved in the recent Operation Unified Response exercise in London, OS staff worked in the control centre to assist with information management.

The map on the right shows the area affected with low water pressure due to burst mains and commercial (red) and residential (blue) addresses. The map on the left shows infrastructure: underground lines, stations, schools, hospitals, emergency services cordon and addresses.


For the purpose of better understanding the pressure points faced by the service and also to review performance, OS delivered data analysis service to NHS England. Below (left) shows the recorded reason for delayed hospital discharges and (right) the distribution of the English over-65 population.


To create a more holistic view of an area for use in the planning, implementation and monitoring of services, OS works with policy makers. As a result, a direct connection between the planning of new residential developments and the availability of health services to these new communities can be secured.

In the examples below: (left) shows Government Indices of Multiple Deprivation and (right) NHS Clinical Commissioning Group data, rail and metro networks, local authority green belt and national park boundary data and the Environment Agency data showing the risk of flooding from rivers and sea.


The following example shows an impactful correlation between self-reported health and wealth. OS worked with local authorities to help them better understand citizen health and income data. The image below shows a mixture of census data from the Office for National Statistics and data taken from the Output Area statistics from the 2011 Census and the Index of multiple deprivation which was published in October 2015. The shaded polygons indicate the % of the population who describe their own health as very good and the residential property is filled with the income decile data with dark red being bottom 10% and dark green top 10%. This visualisation indicates that there is a strong correlation between lower income areas and the number of individuals who are self-reporting poorer health outcomes.


OS data is also widely employed in assisting organisations to better understand their exposure to risk. In this instance, we’re looking at insurance. From a list of addresses with different postcodes (below left) we can show the exposure to potential flood events (below right) and develop a deeper insight on their level of insured risk.


As a policy tool, OS data enables analysis of impact at the most granular (rooftop) level when anything else gives an incomplete picture. In the example below, showing broadband speeds in Bristol, attached houses are placed in different classifications. Such a result undermines all attempts to plan and deploy intervention and remedies.


Finally, some of our data is out of this world and can be used as an interactive experience, see the 3d mars map...




Guest blog from Miranda Sharp, Head of Smart Cities Practice at Ordnance Survey for techUK's "Good to Great Connectivity for the UK" Week.

Get involved at #ConnectedFuture. More information is available on techUK’s Communications Infrastructure Programme.

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