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What's the plan? Transforming services with location data

Transforming Services With Location Data

by Sarah Finch

How can location data - when collected, stored and shared in the right way - improve our local places?

Many of the businesses that have come to embody the internet era, such as Facebook, Google and Amazon are based on data. It is by analysing data that they can understand how users behave, what they want, and the new services that will meet their needs.

Look away from modern technology companies to the public sector, however, and data use has typically been far more limited. Although the move toward open data has increased in recent years, the Open Data Barometer, produced by the World Wide Web Foundation, measured that in 2018 fewer than 1 in 5 government datasets was open to the public.

In this article, we'll take a look at the importance of managing and sharing data at scale in the public sector, and how this can transform our local places.

Delivering workforce testing with data

In the UK, recognition of the importance of data sharing is growing. Chief Data roles are now a common fixture across cities and local authorities, and more initiatives designed to open up data — such as the Public Sector Geospatial Agreement — are coming into effect. Giving organisations access to location data such as this is extremely important, as it enables them to plan and deliver the services that support our local places. From where to build homes, how to provide public infrastructure, and what to do in emergency situations, effective intervention all depends on knowing exactly where things are.

The advantages of a more open approach to data were evident in many areas of the UK's coronavirus response throughout 2020. Gavin Bell, Head of Product Design, was part of a TPXimpact team that delivered the National Workforce Testing scheme at the beginning of the pandemic, supplying organisations that had to operate on site through lockdown with covid testing kits to protect their staff.

“The testing kits were scarce, and they were valuable. We wanted to make sure people weren't taking them for private usage,” Gavin says, “so we needed to send them to employers at their place of work. In order to do this we used two datasets to verify if these organisations were both genuine and based in England, and therefore if we could send the kits to them.”

Location, location, location

Finding out if an organisation is 1) what it says it is and 2) based in a certain location sounds simple enough. But without access to the right data, this kind of task becomes extremely challenging, limiting the services that the public sector is able to provide.

In our workforce testing example, the service relied on the Companies House API, as well as Ordnance Survey data - made available through the Geospatial Agreement. After first checking that organisations were genuine limited companies via Companies House, this was then overlaid with Ordnance Survey data to confirm they were based in England and could therefore receive the kits.

“Finding out if a business is in England is more difficult than it sounds because postcodes can cross borders, plus a company can be registered in one location and have an office somewhere else,” Gavin says. “We, therefore, used local authority data called custodian codes to determine the organisation's location. If businesses using the service fulfilled both criteria, then they would receive crucial covid tests for their staff.”

Data duplication in the planning sector

As this example shows, when we make data available, good things can happen. That said, it is often necessary to collect data from different sources in order to achieve what at face value seems a simple goal.

Dealing with data isn't always going to be easy, but one area where the UK can make significant progress is in the planning system, where large amounts of information are gathered and stored in a highly inefficient way.

Within this complex planning system, data about our local areas and infrastructure (as required for things like planning applications and city plans) are typically held in different locations, inside systems that can't talk to each other, and in formats that are inaccessible — sometimes to both people and machines. This leads to unnecessary costs and the duplication of effort, with the same data having to be collected and analysed again when a new project comes along. It also means that the potential value of this data — to identify areas for innovation or opportunity — is blocked.

By instead breaking down data silos, and storing planning data in single platforms, local authorities can make their data systems much more effective. Greater Manchester's MappingGM tool, for example, provides open access to much of the region's planning, housing, and infrastructure data, as well as proposed interventions — and a way for residents to express their views. This kind of platform also opens up the path toward digital twins and the use of technologies such as AI that can help us analyse the impact of planning decisions on our built environments.

Setting the standard with UPRNs

However, simply making more data more widely available isn't enough. In order to derive value from data, it must be categorised, stored and managed appropriately so that people can actually use it. This is the concept of data standardisation, which we can thank for the emergence of many useful tools, including both newly created datasets and those that have been made fit for purpose in the modern world.

When it comes to location data, one of these tools is the OS Open UPRN. Maintained by the Ordnance Survey, it is a collection of Unique Property Reference Numbers (UPRNs) — unique identifiers for every addressable location in Great Britain. As the website states, 'This may be any kind of building; residential or commercial, but it may also be an object that might not have a postal address — such as a bus shelter or electricity sub-station.'

UPRNs are a crucial part of geospatial data, because — as Gavin Bell notes — there are lots of different ways to describe where things are or where someone lives.

"To use a Scottish example, you could say you live in Glasgow; off Sauchiehall Street; behind the Glasgow School of Art; or 83 Hill St, Glasgow, G3 6NZ," he says.

"On a different project with BEIS we needed to be able to specifically identify a dwelling place, somewhere where someone lives. Happily the long fought for standard, the UPRN, enabled us to do this, as it defines property, even at the level of individual flats that are created when houses are bought and divided."

UPRNs work equally well for commercial properties too.

"Working with BEIS and the OS on this project we were able to bring clarity to identification of a property, rather than relying on addresses or postcodes which vary depending on who writes them down," Gavin says. "Using UPRNs also allowed BEIS to filter out commercial properties for this project by connecting to other datasets. This information was crucial to the success of the project and the delivery of the service."

Time for a walk?

Connecting datasets is an extremely important part of working with data in the public sector, as it isn't always appropriate to pool information in one central location.

“A key aspect of our work is doing data walks,” Gavin says. “We would like to see more areas of government do this — to see how datasets can be connected. It isn't about creating something new or merging one dataset with another. It is just connecting the dots between what's already there. We need that data fluidity in our thinking and in our working because it allows us to do so much more.”

Many people are concerned by the creation of large, centralised databases in government, but it's worth noting that we can unlock value from data in another way. This centres on improving the interoperability of datasets that already exist. Done well, and public sector organisations will be able to join up their services, making them far more efficient in terms of both costs and time, meeting user needs more effectively, and providing a much better experience for citizens as they interact with the government.

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