Digital Twin Definition

The term “Digital Twin” is being used with increasing frequency, but with little consistency, across multiple industries today. Technologies enabling digital twins have evolved considerably, while a simple taxonomy / ontology /vocabulary for the concept itself has not.

To date, there has been no concentrated multi-party effort to harmonize definitions and representations of digital twins in order to put forward a single, authoritative definition to bolster common understanding of not only the base definition of a digital twin, but also its multiple variants and applications.

Digital Twin Consortium will fill this void by recommending a preferred definition, taxonomy, and, ultimately, hierarchy of digital twins to enable the industry to speak with a common vocabulary on this concept – enabling better understanding through shared definition and vernacular. In December 2020, the Consortium released their official definition of a digital twin:

A digital twin is a virtual representation of real-world entities and processes, synchronized at a specified frequency and fidelity.

  • Digital twin systems transform business by accelerating holistic understanding, optimal decision-making, and effective action.
  • Digital twins use real-time and historical data to represent the past and present and simulate predicted futures.
  • Digital twins are motivated by outcomes, tailored to use cases, powered by integration, built on data, guided by domain knowledge, and implemented in IT/OT systems.

Digital Twin Consortium Defines Digital Twin

The foundational elements of the definition are captured in the first sentence: the virtual representation, the real-world entities and processes it represents, and the mechanism by which the virtual and real-world entities are synchronized.

The process involved a cross-section of domain specialists, an extensive review of documentation on the subject, and a stress test of the definition based on digital twin use cases. The result is a definition that leverages established knowledge on the topic, is consensus-driven, and validated against practical considerations.

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