Introduction
This initiative aims to catalyse the progression of urban analytics into Turing 2.0 with the creation of a cross-cutting technology platform for data science innovation in the science of cities and regions. It will leverage world-leading capabilities for research and innovation; and provide a unique bridge from foundational data science to global challenges which are of extreme importance to provide citizens with future urban designs with enhanced levels of sustainability, prosperity and liveability.
Explaining the science
Harmonising components within a single technology layer will encourage greater focus on exploitation of the research engineering capabilities of the Turing and an increased ability to translate fundamental advances in data science and AI into products and tools which address critical real-world challenges. By capitalising on these distinctive assets, Turing engenders a unique resource to support programmes of work with government and commercial partners, and a singular proposition to be leveraged in joint projects with other University partners.
Investment in a cross-cutting resource provides a platform capability which will be leveraged multiplicatively across diverse project streams. An immediate high value return is possible by capitalising on existing research capacity, however this could potentially be scaled back, staged or deferred to manage to a more restrained investment profile.
The work will be delivered by a team which has developed a collegiate and inclusive culture, with high levels of openness and transparency in the production of software and data products.
• Our ambitions are specifically focused towards enhancing the delivery capability of four Urban Analytics missions. (1) New forms of data propel sustainability, equity and efficiency in all forms of Urban Mobility; (2) AI is instrumental to the Land-Use Planning process for buildings, cities and landscapes; (3) Pervasive data are leveraged for healthy, sustainable, and prosperous cities and their populations; (4) Digital Twins are a mature paradigm for the evaluation and implementation of urban policies. These have been articulated and refined through discussion and persistent engagement with our customers, research partners and international peers.
• Outcomes will be measurable: through the adoption of more refined operating models we will seek a minimum of 400% gearing on Turing’s core investment.
• Achievability is demonstrable through established collaborations across every mission with corporates, government, internal programmes (including strategic REG involvement) and university partners.
• The work is enormously relevant to Grand Challenges in Environment, Health and Economy. The importance of a
‘place-based approach to net-zero’ is explicitly recognised in HMG Net Zero Strategy. Connections between place, health and economy are clearly evident in the Levelling Up Missions e.g. in relation to ‘pay, employment and productivity’ in ‘globally competitive cit(ies)’ (Mission 1)’, narrowing the gap in healthy life expectancy (Mission 7), and ‘well-being … improve(ment) in every area of the UK’ (Mission 8). The data science dimension is recognised in the UKRI (ESRC) Strategic Delivery Plan to support ‘world class places’ by providing ‘better data for better policies’ through ‘sustained investment in data infrastructure’.
• The initial timeframe is to advance the city science agenda over 30 months to March 2025.
Project aims
• Capability to exploit data – Proportion (count) of stakeholders reporting that they believe they make better decisions in place-based policy-making
• Product innovation – new products developed; uptake of products and tools by research organisations, business and government.
• Skills and awareness – Proportion (count) of ROs and RWOs reporting that they understand and use advanced data science more effectively than previously
• Research quality – invitation to participate in international events, institutional visits, contribution to ISI-rated journals and other peer-reviewed outputs; citations including software and data products as well as scientific articles; impact case studies.