National Infrastructure Commission: Data for the Public Good


Call for Evidence

New technologies like artificial intelligence and machine learning could help cut delays and disruptions across the UK’s infrastructure network. The National Infrastructure Commission’s report examined the opportunities that these new innovations present, and made recommendations to increase open data sharing to make the most of them. A first Call for Evidence was made on 15 February 2017, with a second following on 27 July 2017.

Summary of the Turing’s submission

The recommendation is made that the government should encourage the uptake of new data-driven solutions to the asset management of critical infrastructures. Potential barriers to rollout include the differing levels of readiness and uncertainty towards integrating new methods into large-scale existing practices. The development of a national ‘digital twin’ of UK infrastructure can help to bridge geographic and sectorial divides, provide a framework for determining sensor locations, and serve as a technology demonstrator for new tools.

The submission also identifies smart traffic management as another key way to utilise data to improve our cities. By deploying open and social media data it is possible to facilitate smart urban management, repurposing existing data created by third parties and the government itself, thus creating ‘lightweight’ smart cities.

Lastly it is suggested that the effective use of big data requires greater standards to make the data accessible and usable. Currently, combining datasets from numerous sources and getting value from them is an arduous task. This would be made easier by having defined and widely accepted standards for data structures, labelling, cleanliness, security procedures, and sharing methods.

Additional information

Weisi Guo, Turing Fellow, University of Warwick
Mark Girolami, Programme Director for Data-Centric Engineering
Darren Grey, Programme Manager for Data-Centric Engineering
Din-Houn Lau, Department of Mathematics, Imperial College
Ricardo Silva, Turing Fellow, UCL
Victoria Stephenson, EPICentre, UCL
Tim Sullivan, Applied Mathematics, Free University of Berlin
Sebastian Vollmer, Turing Fellow, University of Warwick
Daniel Graham, Department of Civil and Environmental Engineering, Imperial College
Scott Hale, Turing Fellow, University of Oxford
Mohammed Elshafie, Department of Engineering, University of Cambridge
Julie McCann, Department of Computing, Imperial College

Turing affiliated authors

Dr Weisi Guo

Honorary Professor at University of Warwick & Professor of Human Machine Intelligence at Cranfield University