What is a ‘digital twin’?

Digital twins are exact virtual models of physical objects, processes or systems. They are typically built from both historical and live data to enable real-time monitoring and modelling of the actual object, process or system or to enable simulation of different scenarios (i.e. ‘what if’ testing and planning).

Digital twins can be used to manage remote operations where the digital twin is advanced enough to enable remote control of the asset or system being replicated. Digital twins of individual processes or objects can also be linked to create complex digital twins of systems, or systems of systems.

A good example of how a digital twin can operate in real life is the creation of a digital twin of a train station using data generated from the actual train station and its immediate surrounds. This digital twin has a vast scope of potential uses:

  • foot traffic data generated from simulating the shutting off or opening of certain entrances can be leveraged to manage the flow of passengers so as to minimise pedestrian congestion during peak hour;
  • simulations of a greater or lower number of level crossings being engaged can be used to analyse how level crossings might be affecting the flow of traffic in surrounding roads;
  • simulations can be run of a train getting stuck on the station to plan for how to ensure other trains can still pass through the station as quickly as possible to minimise disruption to the overall train network; and
  • a digital twin of one train station can be linked to the digital twin of another and changes to one station can be simulated to assess the impact on the other.

Given a digital twin of a single train station could have so many possible benefits, it’s easy to envisage the myriad real-world applications of larger scale and more complex digital twins: from the ability to model the flow of passengers through an entire transport system (not just a train station), a building or an entire city or state, to the production of goods through a manufacturing facility and onwards to their ultimate destination.

Digital twins in Australia

Digital twins are gaining significant traction in Australia, with infrastructure planning, transport, energy and environmental policy and regulation at the forefront of most digital twins projects. In 2019, both the Commonwealth and NSW Governments published guidance materials on digital twins. Indeed, the growing importance of digital twins in Australia is highlighted by the Commonwealth Government’s ‘Australia’s AI Action Plan’ specifically calling out digital twins as an example of AI that is transforming Australia.

The NSW Government has since launched a digital twin of the Western Sydney area, one of the world’s largest spatial digital twins, covering more than half a million buildings, 20,000 km of roads, 22 million trees and 7,000 strata plans. The NSW Government is already takings steps to expand this digital twin to encompass the entire state of NSW and the intention is for the digital twin to be accessible by anyone through a standard web browser. Use of such a state-wide digital twin for bushfire response planning following the Black Summer bushfires of 2019-20 has been one of the key drivers behind the push for its expansion.

Victoria, meanwhile, has embarked on a digital twin proof of concept project in Fishermen’s Bend in Melbourne, while Australia Post recently announced that it is building a digital twin of its delivery network.

What are the legal issues with digital twins?

With so many high-profile digital twin projects in the market and in the pipelines, what potential legal issues do they present?

The Australian Communications and Media Authority (ACMA) recently published a paper on the outcome of research it completed into how digital twins can potentially be used in regulatory decision-making. The ACMA sees digital twins as being a use-case of a combination of the ‘Internet of Things’ (IoT), which broadly refers to the use of multiple wireless and wired interconnections between personal, consumer and industrial devices which exchange data over the internet, AI and augmented reality. As such, the ACMA identified the regulatory and legal considerations relevant to IoT as also being applicable to digital twins.

The risks posed by digital twins will differ depending on the nature of the digital twin and will need to be managed via the contract (or contracts) underpinning the digital twin. Key legal issues to consider in any digital twin project could include:

  • Intellectual property rights: Does your digital twin use third party intellectual property rights? Do you have the right to use them in the digital twin as intended? If innovative new works are created in developing a digital twin, who owns the intellectual property in them?
  • Data use rights: Do you own the data you intend to use in your digital twin? If not, do you have authority from the owner of the data to use it in the digital twin as intended? This is a key consideration even with open-source data, which may be subject to usage limitations. The responsibility and authority of the data-providing parties and their financial rewards could become key negotiation points for digital twins projects.
  • Privacy and data protection: Even if you own data that could be useful in a digital twin, if it contains personal information collected from individuals, do you have their consent to use it in the way intended?  
  • Cyber security: Data from mechanical sensors may present less risk from a privacy / data protection perspective, but increased connectivity brings the potential for increased security vulnerabilities. Who is responsible for keeping the data secure and who bears the risk of cyber events?
  • Malicious use: While the beneficial uses of digital twins are countless, they could also be used for malicious purposes, particularly where digital twins are made public. As an extreme example, digital twins could be used in ransomware or even terrorist attack planning to inflict maximum disruption or damage. What protections are in place to protect against malicious use and who bears any resulting liability? With digital twins anticipated to become increasingly important for infrastructure and governance, malicious actors may in future target digital twins themselves.
  • Responsibility for data quality: How will you ensure that the data is accurate and who bears responsibility for ensuring data accuracy? If your digital twin is intended to model a mission-critical system, is the data you’re using fit for use in mission critical systems? This is particularly key if the digital twin will draw data from multiple, disparate sources.
  • Liability: As with any technology solution – what happens when your digital twin doesn’t work? What loss can you recover if you model a scenario in your digital twin and use it as the basis of a key investment decision, but the digital twin had it wrong? These risks will be particularly important if the digital twin is made up of multiple integrated components or sub-systems.
  • Integration risk: Will legacy infrastructure be an obstacle to integrating the new technology required for a digital twin? Who is responsible for any integration risks?
  • Connectivity and availability: Power outages, software errors, ongoing deployment errors, etc. will impact the overall goal of connectivity between IoT devices. What legal consequences, if any, will there be for outages?
  • Assurance, governance, and trust: Establishing trust in technology can be key to driving uptake. What procedures and mechanisms will be put in place to provide assurance that a digital twin or IoT platform is performing as intended?
  • Standardisation: The current lack of a standardised approach to modelling for digital twins poses challenges for interoperability between digital twins. What standards will be employed in a digital twin to maximise interconnectivity?
  • Ongoing maintenance: Software updates, real-life changes to the physical asset, changes / improvements to the digital twin, etc. means that inevitable ongoing management and maintenance must be factored into the planning, pricing and contracting for digital twins. As is usually the case with their physical counterparts, the cost of such maintenance and management will likely represent the largest proportion of the total life cycle cost of the digital twin.

What’s next?

The ACMA anticipates that digital twins will be more widely developed and deployed in the coming years, given the advancement and growing prevalence of IoT technology combined with the maturation of AI and augmented reality. They identified the communications sector as one example of an industry that might benefit from digital twins in the near future, through the utilisation of IoT to monitor infrastructure and the spectrum environment.

There is a strong global consensus emerging around the importance of adopting open global standards designed to increase both security and interoperability of IoT, which should further facilitate the growth of digital twins projects. Regulatory regimes around IoT (and potentially even digital twins specifically) will undoubtedly have a role to play – whether and to what extent they will facilitate or stifle the growth of digital twins remains to be seen.


Authors: Lesley Sutton, Clare Beardall, Jaron Lam and Luke Standen