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SSRN Electronic Journal
Article . 2025 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2024
License: CC BY
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DBLP
Preprint . 2024
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Foundations for Digital Twins

Authors: Regina Hurley; Dan Maxwell; Jon McLellan; Finn D. Wilson; John Beverley;

Foundations for Digital Twins

Abstract

The growing reliance on digital twins across various industries and domains brings with it semantic interoperability challenges. Ontologies are a well-known strategy for addressing such challenges, though given the complexity of the phenomenon, there are risks of reintroducing the interoperability challenges at the level of ontology representations. In the interest of avoiding such pitfalls, we introduce and defend characterizations of digital twins within the context of the Common Core Ontologies, an extension of the widely-used Basic Formal Ontology. We provide a set of definitions and design patterns relevant to the domain of digital twins, highlighted by illustrative use cases of digital twins and their physical counterparts. In doing so, we provide a foundation on which to build more sophisticated ontological content related and connected to digital twins.

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Keywords

FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Databases, Computer Science - Artificial Intelligence, Computer Science - Information Theory, Information Theory (cs.IT), Databases (cs.DB)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green