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Only very vaguely related pet peeve: the term "Digital Twin" implies that a simulation perfectly matches what is being simulated. This is really almost never the case.

Let's just call them what they are: simulations.

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Digital twins aren't simulations, they're just data. The idea is that it's openly available and easily queryable so that people have good data to run their models and simulations on.

Even real life twins don’t exactly match. No digitization process can be error free, the “digital twin” language is to indicate that it’s supposed to be a realistic model rather than an editorialized/interpreted environment.

But a realistic model for what? The question of what data is important to capture, and how, depends entirely on what you're trying to do with it. The danger of the digital twin narrative is the idea that one model can serve all purposes, which I think will ultimately lead to broken models.

...addendum: ALL models are editorialized/interpreted. Forgetting this often leads to errors.

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