DTAG: A Methodology for Aggregating Digital Twins Using the WoTDT Ontology
Source abstract
Abstract
The advancement of digital twins (DTws) has been instrumental in various scientific and industrial domains, facilitating real-time monitoring, analysis, and optimisation of complex systems. However, it remains difficult to describe precisely the architectural models and their characteristics of DTws and the aggregation of lower-level DTws to higher-level DTws. This article introduces two contributions with the goal of addressing challenges in describing DTws architectures and aggregating DTws. Firstly, it presents the development of “WoTDT” (WoT digital twin) ontology, an extension of the W3C Web of Things descriptions ontology, designed to semantically describe the five-dimensional model architecture of DTws. This ontology enhances data interoperability and accessibility across dimensions, promoting a deeper understanding of DTws. Secondly, it introduces the “DTAG” (digital twin aggregation) methodology for aggregating multiple DTws into an unified DTw aggregate (DTwA). This methodology considers whether the DTws contain semantics or not and employs the WoTDT ontology to conceptualise the architecture and features of the resulting DTwA. Finally, an example of WoTDT ontology together with the DTAG methodology is shown in the context of the European H2020 construction-related project COGITO.
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Research context
OpenAlex topics: Digital Transformation in Industry
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Ontology Engineering Group, Universidad Politécnica de Madrid, 28660 Madrid, Spain
Funding
Multiannual Agreement with the Universidad Politécnica de Madrid
References (57)
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