The Geospatial Commission asked me to write a blog post for them following on from their open identifiers announcement. First thought was what a great honour! But then my second thought was, what messages do I really want to land with readers in this space?
In light of this, I have to start with an apology for the fact you are going to go for an amble through my mind on an early morning dog walk with Toby (the very cute and naughty cockapoo). This is really the stuff I think through most mornings as he plays in the park.
My background is town planning and planning law, so I am very biased about how I approach the issue of data. There are great leaps taking place under the banner of planning technology, particularly in how users' interface with the planning system (think 3D, submissions systems and consultation), but the challenge for planners is actually getting their hands on cold hard data. Data that tells them the impact the planning system is having, and perhaps more importantly what they need to do to change the outcome.
I have to defend the planning system for a moment, I do not, and would not ever argue that the planning system is broken, but I do argue that using it more effectively we can achieve more for our communities.
Built environment data, the last bastion?
It constantly amazes me how limited an insight we have into how we live, and how changes we make to the built environment really impact on our living environment, health, services, movement and the climate crisis.
Away from the built environment, the world of ‘Big Data’ already enables us to predict with some certainty how changes to business might impact customer behaviours, how credit histories may impact future outcomes in financial transactions and numerous other great examples. Yet in the built environment, this has not yet been grappled with.
Whilst this is not the right space to do a full review, there are companies in the market that have done some great work in this space, enabling the automation and review of development opportunities and viability. As a public service we need to be looking at how we can buy in to, and in the right places, lead this work.
Data in isolation
One of my key learnings (and I hope everyone recognises the same) is that it is all well and good reviewing how we collect data, however, the silo approach to data limits the benefit of data collection to the data collectors and perhaps a few others. In my view, and the view of many others, this is because the data sets are constructed in ways which limit their ability to be connected to one another. It is only when these data sets can be connected together, do we start to get real insight into what the data is really showing us.
To take a simple example of the challenge of linking datasets we can look at ‘which house was built under which planning permission’:
To those outside of the planning system, this might seem obvious, but for those of us inside it, the data is held in unnecessary complex formats for a number of reasons:
- Developers might have multiple consents for the same site.
- Planning and Building control services may be operating on different back-office systems.
- De-regulation of systems means that the type of data available may be incomplete.
- There is a lack of granularity in the data.
- Sometimes builders just ignore what they have consent for.
There are a multitude of other variables. However, the key message from this is that due to both data quality and lack of obvious connection between the data sets, even a simple question in some cases can be very difficult to answer.
So, with that in mind, if we were to ask some of the more difficult questions about outcomes as a result of planning decisions alone, they become nigh on impossible to answer.
To take a more complex challenge – ‘What is the net increase in impact on air quality from new development granted planning permission in London each year?’
The amount of data sets you would need to answer this are vast, but important. The challenge remains exactly the same, in that until all of the data sets have easily identifiable linkages, the level of insight needed is nigh on impossible to achieve in a meaningful and consistent way. Anyone who says they have the answer (rather than a best guess) is either extraordinarily clever, or speaking in generalised terms.
The point is that by addressing how we identify and structure the data, we can start to unlock some of the greatest challenges of our time, and from a town planning perspective, start to plan for our communities in a far more holistic way, rather than the current silo or single-dimensional way we are currently forced into, due to the data that we use.
Making data more accessible
I can’t talk about data relating to communities without taking the opportunity to highlight the great work that is being done in the world of open data to make data more accessible for users. I would argue that nowhere is it more important to push this principle than in the geospatial world.
Data relating to where we live, the environment we live in and how it is changing should by its very nature be a shared resource, and accessible by everyone. I appreciate that not everyone will want to use it, and for many of us, they are datasets that require interpretation in order to achieve behaviour changing insight. To achieve this, data may need to be commercialised in multiple ways, which opens whole new challenges and discussions. However, the very principle of it being a public asset changes peoples relationship with it, and how citizens view its trustworthiness.
There are many projects taking place in London that are starting to open up spatial data for Londoners. I must give a plug for colouringlondon.org as an exemplar for this, as both a platform where users can supply their own data to a space where everyone can see it and opening up data sets that are often hidden away in computer systems. Other fantastic resources include the London Data Store, and the Planning London Data Map, and the soon to be launch Planning London datahub all of which operate with the express intention of enabling citizens to have data we hold readily accessible to them.
Are UPRNs and USRNs the answer?
You can’t write a blog for the Geospatial Commission without celebrating the amazing work they have been leading the charge on, unlocking UPRNs as a public data set. Read more here on this week’s announcement and the low down from Geoplace
My hope is that as a result of this, we can get both public and private bodies to use UPRNs and USRNs as a categorisation tool. This will enable us to very quickly link together datasets with certainty that we are comparing the same data sets.
Are these perfect, well no. Is anything? There are challenges about how far they go, the relationship between UPRNs, the point in the development process they are created, and interrelationship with other data sets, to name but a few. But we must as an industry stop and celebrate this as a massive leap in the right direction.
The change I believe we will see initially is the ability of public bodies to use the data they hold to gain insight into how best to deliver services. The ease of linking data making it more straightforward and less costly to deliver user-centred service design, based on real facts. We will also see a greater expectation from our elected representatives to be given evidence-based facts and trends, upon which professional opinions are based. This is going to be transformational.
Should we have done this sooner? Who knows? But in practice we are here, there is no doubt that COVID19 has taught us that evidence-based decision making is the way forward. Will UPRNs and USRNs be the answer, not sure, but what I can say with certainty is they will definitely help us on our way.
Thank you Geospatial Commission, MHCLG, Ordnance Survey and everyone else who contributed to this massive change. We appreciate it!
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Comment by Andy Mabbett posted on
I wonder why then, in the last week, the Environment Agency have stopped using UPRNs in their flood warning pages for properties in England?
The example archived here (like all others) no longer works: