Digital twins are virtual representations of physical ‘real’ objects and systems which have been widely applied in the engineering realm for tasks such as engine optimization and port management.
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The four foundational elements to support digital twins are:
the Physical or Real Twin (in this case the ocean or a part of it);
the Data Lake filled by all kinds of observations and information that are needed to create and continuously update the Twins;
the Digital Twin itself, which includes model(s) with access to the Data Lake, analysis and insights to support decision-making tools;
the Interaction and Decision support tools enable decision making which include visualisation capabilities and customizable digital interfaces.
Digital twins are designed to support decision-making and to make well-timed interventions that provide better outcomes. Thus, it is not only the Digital Twin that is important, but also the ease of creating actionable information or decisions (often that in turn influence the Real Twin), through policy, management or operational decisions. This implies the need for a well-formulated interface between the digital twin and a machine or human.
Digital Twins and ocean forecast models are often confused, but there are clear distinctions. Digital Twins include predictive and data driven models focussing on interventions and thus provide answers to ‘what if’ questions. They have user interaction embedded in their design, including visualisation, user driven data transformation and data sciences tools.