Connected digital twins must provide determinable insight into the built environment. Better insight based on better data will enable better decisions and lead to better outcomes for the public. [1].

In the case of infrastructure, insights could be capacity, location, condition, value, usage, performance, service level, and the environmental, social, and economic impacts of existing and proposed infrastructure.

Connected digital twins can be instrumental in achieving measurable improvement by providing insights into the performance and enhancement of the built environment.

Mechanisms - how to embed Insight

Benefits Realisation Framework

As mentioned in the report Gemini Papers: How to enable an ecosystem of digital twins? [3] and suggested in Digital Twin: Ethics and the Gemini Principles , to monitor and evaluate progress, a Benefits Realisation Framework is needed, which would allow insight on the interventions. This framework would include Key Performance Indicators (KPIs) to measure the progress and benefits of connected digital twins, along with governance arrangements to support data capture, management, and dissemination.

Synthetic Environments and Living Labs

Synthetic environments, as presented in the report Cyber-Physical Infrastructure Vision [5] are a collection of digital modelling technologies that includes simulations, emulations, and visualisations, are instrumental in creating digital synthetic models. These models allow for exploration of behaviours and characteristics of products and services. AI plays a crucial role in these environments, providing intelligence within smart machines and using these environments to identify insights and optimizations. In the context of the Insight Gemini Principle, these Synthetic Environments and AI tools enable us to derive determinable insights into the built environment, facilitating superior decision-making and improved outcomes.

Whilst much of the iteration of design and test can be performed in synthetic environments, eventually the real world must be used to refine designs to work with real physics, sensor noise and couplings that are often not possible to model [5]. Living labs are used for socio-technical development, testing on public acceptance, privacy, security, ethics, and trust. They use a "learning by doing" approach, delivering real services to real customers and involving real people and situations [5].

Modelling and Simulation, Analytics, and Visualisation

A Reference Architecture is part of the backbone of the operation of digital twins, as mentioned in the Digital Twin Navigator [4]. This architecture is layered, including Data Acquisition, Data Transmission, Data Management and Integration, Modelling and Simulation, Analytics, Visualisation, Control, and Service. The Data Acquisition layer involves IoT devices, sensors, control systems, SCADA, networks, and more. These components work together to capture valuable data from the physical system. Once acquired, Data Management becomes critical. This involves the use of web services or network communications gateways and secure data lakes for storing and organizing the data (data management technologies include: BIM, Geographic Information Systems, Semantic Web & RDF [3]).

As the Digital Twin Navigator explains in further detail, middleware acts as an interface layer between raw data and useful information, while analytics tools (AI, Machine Learning, Predictive Analytics [3]) crunch numbers and draw conclusions [4]. Modelling and Simulation, Analytics, and Visualisation layers interpret the data and provide actionable insights. This is where raw data is converted into comprehensible formats [4]. These tools and mechanisms are not just add-ons but essentials for the effective functioning of digital twins [3].

Skills and Competencies for Insight

To establish a strong skill set within the team, competency scorecards presented in the Skills & Competencies Framework are a valuable tool. These scorecards will help identify skill and competency gaps, build cross-functional teams, and develop a resource plan and pipeline of skills needed over a specific time frame [6].

Relevant skills for the Gemini Principle of Insight are Analytics and Intelligence skills. They involve specifying data quality requirements, structuring and analysing data using statistical analysis and other data science methods, and using visualization techniques to aid decision-making [6]. Some roles that utilize these skills include Data Custodian, Benefits Manager, and Digital Twin Architect [6].

Ethical considerations

The report on Digital Twin: Ethics and the Gemini Principles highlights three key ethical implications related to the Gemini Principle of Insights: making sure insights create value and provide real progress, enabling transparency of the whole process starting from gaining insights to making decisions, and facilitating accessibility to make sure insights are understandable and interpretable by all stakeholders.

Examples

The use case and case studies outlined below demonstrate the practical applicability of digital twins across various industries and sectors in the context of the Insight Gemini Principle.

Use Case

A use case in the context of the Gemini Principle of Insight:

• Regional Resilience, response and simulation [7]: An integrated digital twin can enhance regional resilience by mapping interdependencies and simulating disasters. When key infrastructure like bridges in Cumbria failed during floods, the impact was severe and widespread. The necessary information to anticipate these risks existed but was scattered across different organizations. A digital twin could integrate diverse data, such as transport infrastructure, socio-economic factors, and environmental models, to simulate and prepare for such events. This aligns with the Gemini Principle of Insight by providing actionable insight to make superior decisions, ultimately improving public outcomes. The digital twin could also be used post-interventions to measure impact, justify investment, and iteratively improve the model over time.

The Digital Twin Navigator [4] provides examples of primary and secondary use cases for digital twins in the context of asset management.

Case Studies

The case studies outlined below demonstrate the practical applicability of digital twins across various industries and sectors in relevance to the Gemini Principle of Insight.

• CReDo, which particularly emphasizes the importance of collaboration, public good and federation through interconnected data sharing.

• Ocado Case Study: Ocado, a leading online grocery and tech company, utilizes a cyber-physical platform where various technologies including AI/ML and digital twins are integrated. This allows the company to enhance operations such as fraud detection, demand forecasting, route optimization, and order assembly. Digital twins, fuelled by real-time sensor data, optimize warehouse operations. These technologies, contributing to Ocado's competitive advantage, align with the Gemini Principle of Insight by providing actionable insight into the operational environment, facilitating superior decision-making.

Please see the DT Hub case study register (Case Studies - DT Hub Community (digitaltwinhub.co.uk) for further evidence of successful outcomes with digital twins.

References

[1] The Gemini Principles. Available at: https://digitaltwinhub.co.uk/files/file/12-gemini-principles/. Accessed March 18, 2024.

[2] Digital Twins, Ethics and the Gemini Principles. Available at: Digital_Twins_Ethics_and_the_Gemini_Principles.pdf (utwente.nl) Accessed March 18, 2024.

[3] Data for the Public Good. Available at: Data for the Public Good - Public Resources - DT Hub Community (digitaltwinhub.co.uk) Accessed March 18, 2024.

[4] Digital Twin Navigator. Available at: Digital Twin Navigator - Public Resources - DT Hub Community (digitaltwinhub.co.uk) Accessed March 18, 2024.

[5] Cyber-Physical Infrastructure. Available at: assets.publishing.service.gov.uk/media/6204e6ebe90e077f7392d446/cyber-physical-infrastructure-vision.pdf. Accessed March 18, 2024.

[6] Skills and Competency Framework. Available at: Skills & Competency Framework - Public Resources - DT Hub Community (digitaltwinhub.co.uk) Accessed March 18, 2024.

[7] The pathway towards an Information Management Framework - A ‘Commons’ for Digital Built Britain. Available at: The pathway towards an Information Management Framework - A ‘Commons’ for Digital Built Britain (cam.ac.uk) Accessed March 18, 2024.

[8] Digital Twin Toolkit. Available at Digital Twin Toolkit - Public Resources - DT Hub Community (digitaltwinhub.co.uk) Accessed March 18, 2024.

Further Reading

• The Gemini Principles

• Our Vision for the built environment

• Data for the Public Good

• Flourishing systems

• Skills and Competency framework

• Pathway towards and IMF

• Digital Twins, Ethics and the Gemini Principles

• Digital Twin Navigator

• The Cyber-Physical Infrastructure Vision

• Our Shared Understanding

• Trust, Purpose, Value and Connected Digital Twins

• Gemini Papers: What are connected digital twins?

• Gemini Papers: Why connected digital twins?

• Gemini Papers: How to enable an ecosystem of connected digital twins?