Planning and Housing Landscape Review
Despite a wealth of available geospatial data in the UK, standardisation, access, awareness and skills remain a major barrier, the Geospatial Commission reported

UK ‘lacks skills to unlock’ geospatial data potential in planning

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Karl Tomusk

A lack of geospatial data standards and a shortfall in skills are stifling opportunities to solve the housing crisis, a report from the Geospatial Commission has found.

Data innovation across housing and planning could help more homes to be built where people want them, according to the Planning and Housing Landscape Review, adding that accessing and using data remains a challenge.

Although there is a “vast array” of geospatial data available in the UK – including local development plans, local authorities’ land and property gazetteers, Land Registry data, utility asset and topographic data – the quality of the information, as well as accessibility and available skills constrain how it can be used.

A historical lack of common standards has meant related datasets can be incompatible. As a result, working with raw geospatial data can still be a time-consuming, manual exercise.

The report found that companies outside proptech struggle to recruit staff with the skills they need to interpret and manipulate geospatial data.

Some 60% of local authorities interviewed for the report said a lack of relevant skills and resources was one of the top three barriers to their maximising the value of geospatial data.

The report’s authors also identified a widespread lack of awareness of that value. There is a need, they said, to showcase “the art of the possible” – such as case studies with associated ROI measures – and make advocates of key decision-makers in the public and private sectors.

The report set out four steps needed to “unlock the value of geospatial data”:

  1. Standardisation: the value of geospatial data is in bringing together diverse datasets to build a more holistic understanding of the relationship between people and places. The report called for a standardisation in the metadata and the schema within, and possibly across, sectors.
  2. Develop and implement plans in collaboration: with better standardisation, there is an opportunity to encourage more information sharing among organisations involved in planning and housing locally, regionally and nationally.
  3. Accessibility: before value can be derived from geospatial data, it needs to be made more accessible. Barriers include data protection regulations, commercial sensitivities and staff capacity. Respondents to the report suggested the government could play a role in identifying data sets that could be released and promote data sharing within the private sector.
  4. Address the skills and resource gap: local authorities do not have the resources they need to invest in the space, and the problem goes beyond councils. A wide range of sectors – largely outside proptech – have few resources for geospatial staff, and where they do, they might be missing data science and programming skills. Data scientists need to be made aware of the opportunities in the housing and planning sectors, while training is required for those already in the industry.

Andrew Trigg, director of digital, data and technology at HM Land Registry, said: “This report recognises the value and potential of making data more easily available at both the local and national level, and HMLR supports efforts to make data more findable, accessible, interoperable and reusable.

“We’re excited to continue our work to grow and enhance freely available data to further strengthen its impact on the wider economy.”

Thalia Baldwin, director of the Geospatial Commission, added: “We have published this review of the housing location data landscape to help make it easier to understand what is happening in this complex area.

“The Geospatial Commission will be working with the Ministry of Housing, Communities & Local Government, Homes England, HM Land Registry and across the housing and planning sector to consider our collective priorities for location data improvement.”

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