Digital twins are now well established in a number of domains and are increasingly being linked into ‘Ecosystems of Digital Twins’ (EDTs), but foundational challenges remain.

Faced with the challenge of twinning systems that are spread across spatial and temporal scales with their digital avatars motivates the adoption and development of a system of multiple interconnected digital twins, naturally organised into a hierarchy, incorporating digital twins at the component, asset, system and process levels. To extract value from this hierarchy would require a means for these digital twins to combine resources and information to provide insight and analytics beyond the capabilities of the individual components. The ‘system of systems engineering’ (SoSe) approach provides a natural framework in which to design systems of networked digital twins in a scalable manner and which are able to provide unique insights only possible at the collective scale.  

This project is supported entirely by public funds, through Wave 1 of the UK Research and Innovation Strategic Priorities Fund, under EPSRC Grant EP/T001569/1.

Explaining the science

The project brings together multidisciplinary expertise from across the Turing community, including in urban analytics, complex systems engineering and economics.

The Ecosystems of Digital Twins project consists of five work packages:

1. Digital Twins for Fleets and Supply Chain Management

The aim of this work package is to leverage a ‘Systems of Systems engineering’ approach for fleets. The successful outcome of the proposal will be the development of a translatable methodology for designing scalable digital twin ecosystems for large fleets, be they aircraft engines, robots in a warehouse or ships transporting goods. This relates naturally to the future of mobility.

2. Developing the National Digital Twin

The aim of the National Infrastructure Commission’s recommendation to develop a national digital twin is to build a tool which would help us understand, manage and plan our infrastructure better. The vision is that, rather than one huge singular digital model, the National Digital Twin should comprise a wide range of twins of different infrastructure assets and systems joined together in a secure and resilient way. The aim of this work package is to overcome fundamental obstacles which preclude the development of a National Digital twin, as well as demonstrate how to leverage, develop and deploy systems of digital twins for built infrastructure at the building, regional and city level.

3. Digital Twin for Communities and Healthy Cities 

The aim of this work package is to extend this vision of the National Digital Twin into modelling of society at the city level, developing digital twins for improved service delivery, drawing on connections between health, education, crime and housing.

4. A Digital Twin for the Economy

The need for the ability to effectively twin complex systems has been identified in other sectors. In economics, the need for effective monitoring and scenario testing tools motivates this work package, which builds on ongoing work by the Finance and Economy programme.

5. Foundations of Ecosystems of Digital Twins

These projects face challenges of a foundational nature. It is becoming increasingly clear that Artificial Intelligence and Machine Learning are playing key roles in enabling these technologies, along with recent developments in Computational Statistics and Mathematical Modelling. To provide a critical mass of expertise, and enable translational research, this work package aims to work closely with the four other project teams, as well as with other AI for Science and Government projects as is needed.

Project aims

The overarching aim of the project is to develop new methods, tools and underpinning foundations to build well-defined EDTs which are spread across spatial and temporal scales, addressing specific use cases in engineering, health, commerce, economics, urban infrastructure and community modelling, as identified by relevant commercial and government stakeholders.


The National Infrastructure Commission has identified the need for a National Digital Twin, as an "ecosystem of digital twins that are connected by securely shared data". Recent experience has demonstrated a need for policy modelling tools and an appetite for collaboration amongst government and business to face challenges in health, social and economic well-being, and commercial and built infrastructure.


Researchers and collaborators

Professor Ben MacArthur

Director of AI for Science and Government, Deputy Programme Director for Health and Medical Sciences, and Turing Fellow