The challenges and legal implications of digital twins

Catherine Simpson explores some of the challenges to the adoption of digital twins and considers how they might be addressed in construction contracts.

The concept of the digital twin is gaining momentum in the construction industry. Its potential applications look set to transform the way in which owners and operators design, construct, maintain and manage their assets. But what are the legal implications of digital twins? We explore some of the challenges to their adoption and consider how they might be addressed in construction contracts. 

What is a digital twin?

A digital twin is a digital replica of a physical asset, process or system in the built or natural environment. Unlike other models, a digital twin typically uses real-time data from various sources, such as sensors placed on the physical twin, and applies advanced analytics, machine-learning and artificial intelligence to replicate real-world situations. Thus, the digital twin can be used to predict how the physical asset, process or system will react to changes. 

To date, most applications have taken place on a relatively small scale. However, the Government is promoting the development of a national digital twin that will capture all UK infrastructure.  Therefore, it seems inevitable that we will see digital twins being developed on a much larger scale and becoming increasingly influential. 

What are the legal implications of digital twins?

At the most basic level, a digital twin could simply act as a central repository of information, incorporating data about how a specific asset – say a building – has been designed and constructed, into which further data is added about how it performs and ages over time. This could be used to inform the management, operation and maintenance of the building. 

However, at the most advanced level, a digital twin could be something far more complex and multilayered, incorporating virtual projections of almost anything. This is the scale which the UK government is advocating – an intricate model of our current infrastructure which could be used to inform decisions and test solutions to population growth, congestion, climate change, you name it. A model of this complexity would be very challenging for a contractual framework to govern. Issues such as data ownership, causation and liability could all potentially be unclear, difficult to unravel, and contentious. 

Data ownership 

In many cases digital twins may incorporate copyright material, meaning that the intellectual property provisions of contracts will need to be updated to reflect the now wider range of use of the data for the digital twin. In some cases, this may be as simple as including the digital twin within the contractual definition of permitted use, but this will vary from contract to contract. 

Any licence granted in relation to use of the data should be for a suitably long period so as not to expire before the end of the life of the twin. This is likely to be the full life cycle of the asset, process or system, so potentially many years.

There also needs to be legal clarity on who is the rightful owner of the data held within the model. It is important that the rights of individual parties making a distinct contribution continue to be recognised, particularly where the data shared incorporates copyright material. However, complex situations may arise where more than one party have contributed, as the end product of the data sharing might result in a situation of joint ownership. 

Unless there are specific contractual provisions covering this, the rights of joint owners may not be clear. Further, if ownership of the individual data contributions sits with the party who shared the data, where does ownership of the digital model as a whole lie? This will need to be established.

Data sharing and confidentiality

By their very nature, digital twins rely on data sharing, and the contracts that govern them must allow for that. This runs contrary to current norms that oppose non-essential sharing of data. However, this prevailing cultural resistance to data sharing, particularly where the benefits of doing so are technical, complex, or difficult to understand, must be broken down if the full benefits of digital twins are to be realised. The case will need to be made (where it can be) for the perpetual benefits to the public, as a legitimate reason for sharing data.

There is a related issue of confidentiality. Given the number of stakeholders who may have access to the digital twin, some parties may not feel comfortable with sharing confidential information, such as trade secrets. This may be further compounded by the fact that with any data-sharing platform there is always a risk of security breaches and data losses, and any vulnerabilities associated with such systems will increase substantially when different digital twins are amalgamated.

Where the data is considered to be confidential, appropriate non-disclosure clauses may be required within individual contracts, or a project-wide confidentiality agreement may need to be signed by all the parties. Where there are many users of the twin, different access permissions may be required to allow confidential data to only be viewed by certain users. Similarly, some parties may request the redaction of certain data. However, this should be proportionate. Although it may not be essential that all information be embedded into the model, a digital twin will only ever be as good as the data that goes into it. 


Probably the most complex issue to touch on is that of liability. Digital twins are interconnected systems in which changes in one item of data will impact other parts of the model, and as the digital twin evolves, more and more parties may be using and relying on data that could include errors. In situations where there are multiple parties and data sources, the digital twin is likely to require a single organisation to act as gatekeeper to the data, to prevent unauthorised changes. However, where there is an error, it may still be difficult to establish where the liability lies. 

Equally, the blame may not lie with one party alone, or it may be hard to prove that the original data provided was not of sufficient quality to begin with. The fact that different parties are relying on the accuracy of data provided by one another may also lead to trust issues.

The Gemini Principles, a series of values published by the Centre for Digital Built Britain’s Digital Framework Task Group to guide the creation of the national digital twin, place heavy emphasis on clarity of purpose, trust, openness, quality and the effective function of the twin. 

Given the complexity of potential liability issues, it would be beneficial to ensure that all contracts are clear about the purpose and function of the data, perhaps with reference to the Gemini Principles, with the aim of fostering trust between the parties involved and to encourage the sharing of data which meets the same high standards.

The NEC suite of contracts, which provide that parties must act in a spirit of mutual trust and cooperation, is certainly evidence that contracting can encourage more collaborative and open ways of working. Although it may be difficult to enforce such obligations (especially given the common law stance that neither party must act in good faith), having clear terms of reference may go some way to avoiding disputes between the parties later down the line. 


The range of potential legal issues will no doubt expand as the use of digital twins evolves. There will be project-specific legal considerations depending on the intended use of the digital twin, as well as issues of data ownership and liability which will need to be addressed in the relevant contract. Further, as the success of the digital twin depends to a large extent on close collaboration by all, this could be encouraged within the contractual terms themselves. 

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