Semantic Interoperability in Federated Digital Twin Systems: A Systematic Review Through the Levels of Conceptual Interoperability Model

Abstract:When two companies connect their digital twins, software models of their plants kept up to date with live data, each twin must translate the other's data into its own terms, and that translation rule, called a mapping, can stop being correct when one company changes the meaning of its data without telling the other. This PRISMA 2020 systematic review screened 5,833 records and read 119 full texts to determine whether any published system detects such a broken mapping and repairs it while the twins operate. In all 32 included studies the mapping is fixed before operation, and the two ingredients of run-time repair appear only separately: cross-company matching without any check that the match still holds, and detection and repair of changed meaning within a single company. The review turns this gap into six requirements, each illustrated on one running example, that a system claiming run-time semantic interoperability between independently owned twins should meet.

Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Systems and Control (eess.SY)

arXiv:2611.02125 [cs.SE]

(or arXiv:2611.02125v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2611.02125 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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