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MHCLG digital chief points to attribute exchange potential

25/05/18

Paul Maltby outlines thinking on data for local government services and priorities for departmental team

Local government should be looking to a different model of using data, with an emphasis on attribute exchange, to support its transactional services according to one of government’s leading figures in the field.

Paul MaltbyPaul Maltby, chief digital officer at the Ministry for Housing, Communities and Local Government (MCLGH), outlined his thinking at the Nesta City Data Analytics conference, along with indications of his team’s priorities in supporting local government.

He said that, while there are immediate priorities to improve the data infrastructure used by local authorities, they should be looking at the possibilities of attribute exchange. This involves a citizen providing consent for them to check on specific attributes of their personal data, such as age or qualification for benefits, to validate their eligibility for a specific service.

“For transactional services we should be moving to a different pattern that is much more based on attribute exchange, not just because it is more efficient but because it starts to build in more privacy protection and trackability of what we are doing and why,” Maltby said.

“Even in central government this process of personal data exchange is only beginning. HMRC has some nice examples with place like the Home Office and the external market of people who do tax services in the private sector.

“I think the potential in local government for this type of work is huge, but I don’t see a huge amount going on and it’s important we realise that we have to update our methods to keep pace with change. If we’re relying on transactions with amalgamations of data from different services we are probably not doing something right.”

Improving infrastructure

The more immediate priority, however, is to get the basic data infrastructure into better shape.

“I’ve spent some time trying to bring together the community of data scientists to amplify their knowledge and the work going on, but as for the vision of local authority data I want to anchor it at the other end of the scale. If we need a simple vision, I think it’s time for us to fix our plumbing,” Maltby said.

He emphasised the importance of initiatives such as the work, led by the Government Digital Service, on building registers as a canonical list of data for all of government; and the further development of standards to support the data architecture.

With the MHCLG providing central oversight and support for local government, he pointed to two areas in which the digital team is working.

One is in working out technical service patterns that could help councils build services on successful models.

“We know local government services are different, but also that there are a lot of things in the design and components that might be used for a number of citizen facing and other services in local authorities,” he said. “We can take the pain out of people moving from that old world to more user led design and component architecture.

“We’ll be working on that and trying to find a space where we can share that knowledge and patterns bottom up.”

Digital land

The second element is in the work on “digital land” – the improved use of geospatial data highlighted in the Conservative Party’s 2017 election manifesto –  with an emphasis on improving diversity in planning and house building by improving access to and usability of the data.

He acknowledged that the data can be hard to find, citing the example of tracking down all the data on tree preservation orders. This can make it difficult to build services that need to take these into account.

Other possibilities include the potential for incorporating machine learning tools within core services, so they could provide data analysis as part of the service delivery. Maltby cited the possible example of compiling rotas for social care workers.

He also reiterated the importance of data ethics and said a new version of the Data Science Ethical Framework is under development.

Image from GOV.UK, Open Government Licence v3.0

 

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