Digital twins are a rapidly growing area of research that combine models and data to provide up-to-date information about a system's state. They support reliable decision-making in fields such as structural monitoring and advanced manufacturing. Metrology data can be used to update models, offering benefits in metrology itself. The digitalisation of metrology provides an opportunity to make metrology data 'twin-friendly' and integrate digital twins into metrological processes. This paper discusses key features of digital twins for metrology, highlights links between digital twins and virtual metrology, and outlines how metrology can use digital twins and support their use. It also suggests potential future developments to maximise benefits. Digital twins involve a real-world object, a model of its aspects or behavior, and data to ensure the model reflects the object's current state. They are useful for understanding an object's state based on recent data, leading to benefits in areas like structural health monitoring and advanced manufacturing. Digital twins can also help in high-value, low-volume manufacturing by designing assemblies based on individual part performance. Digital twins can use metrology data for model updates, and metrology can support digital twins by ensuring data reliability. The paper explores how digital twins can be used in metrology, including applications in measurement apparatus, objects under test, and calibration. It also discusses the role of metrology in supporting digital twins, such as improving confidence in twin outputs through SI units and traceability. The paper highlights the importance of metrology in digital twins, including the use of SI units, traceability, and uncertainty evaluation. It also discusses the development of digital frameworks for metrological data communication and the potential of digital twins in various sectors, including manufacturing, power generation, and construction. The paper concludes that digital twins can benefit metrology by improving system understanding and decision-making, while metrology can support digital twins by enhancing data reliability and consistency.Digital twins are a rapidly growing area of research that combine models and data to provide up-to-date information about a system's state. They support reliable decision-making in fields such as structural monitoring and advanced manufacturing. Metrology data can be used to update models, offering benefits in metrology itself. The digitalisation of metrology provides an opportunity to make metrology data 'twin-friendly' and integrate digital twins into metrological processes. This paper discusses key features of digital twins for metrology, highlights links between digital twins and virtual metrology, and outlines how metrology can use digital twins and support their use. It also suggests potential future developments to maximise benefits. Digital twins involve a real-world object, a model of its aspects or behavior, and data to ensure the model reflects the object's current state. They are useful for understanding an object's state based on recent data, leading to benefits in areas like structural health monitoring and advanced manufacturing. Digital twins can also help in high-value, low-volume manufacturing by designing assemblies based on individual part performance. Digital twins can use metrology data for model updates, and metrology can support digital twins by ensuring data reliability. The paper explores how digital twins can be used in metrology, including applications in measurement apparatus, objects under test, and calibration. It also discusses the role of metrology in supporting digital twins, such as improving confidence in twin outputs through SI units and traceability. The paper highlights the importance of metrology in digital twins, including the use of SI units, traceability, and uncertainty evaluation. It also discusses the development of digital frameworks for metrological data communication and the potential of digital twins in various sectors, including manufacturing, power generation, and construction. The paper concludes that digital twins can benefit metrology by improving system understanding and decision-making, while metrology can support digital twins by enhancing data reliability and consistency.