A Meta-Framework for Virtual Entities Within Digital Twins: Better Understanding for Stakeholders and Technologies

Digital Twins (DT) represent a transformative technology that bridges the physical and digital worlds. The rapid advancement of DT, providing a virtual representation of a physical asset called Virtual Entity (VE), has led to the development of various DT solutions. However, research indicates a lack of a unified understanding of the VE’s role among stakeholders, creating challenges when comparing existing DT frameworks, technologies, and components. This paper introduces a meta-framework encompassing three main concepts: First, it defines specific perspectives to cover all aspects of the VE. Second, it introduces levels of abstraction to identify underlying features and models of existing technologies, as well as integrate stakeholder views represented through cognitive mental models. Third, through the concept of interlocking the perspectives downward the levels, it recognizes the interconnected nature of technologies at an implementation stage and enables the alignment between mental models and current technologies and frameworks. As a tool, the meta-framework serves three main functions: First, it provides insights and knowledge about VEs within existing frameworks. Second, it allows for their comparison. Third, it promotes the reuse of existing components as a groundwork for DT development. By applying the meta-framework to three commonly used DT frameworks, we can extract their single features and models and place them within the context of the VE. This analysis reveals that certain VE representations lack behavioral models, a key concept of DTs. Furthermore, based on an industry-specific use-case, mapping the mental models of specific stakeholders to existing technologies lays the groundwork for new DT solutions. Overall, the presented meta-framework promotes a unified understanding of VEs that is independent of technology and stakeholder specifics.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3589787
Citations
1
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
1.24
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article

A Meta-Framework for Virtual Entities Within Digital Twins: Better Understanding for Stakeholders and Technologies

René Hofmann, Lukas Kasper, Gernot Steindl, Christoph Klaassen
1 citations
IEEE Access
Digital Transformation in Industry
1.24
article

A Meta-Framework for Virtual Entities Within Digital Twins: Better Understanding for Stakeholders and Technologies

René Hofmann, Lukas Kasper, Gernot Steindl, Christoph Klaassen
article en
1 citations

Abstract

Digital Twins (DT) represent a transformative technology that bridges the physical and digital worlds. The rapid advancement of DT, providing a virtual representation of a physical asset called Virtual Entity (VE), has led to the development of various DT solutions. However, research indicates a lack of a unified understanding of the VE’s role among stakeholders, creating challenges when comparing existing DT frameworks, technologies, and components. This paper introduces a meta-framework encompassing three main concepts: First, it defines specific perspectives to cover all aspects of the VE. Second, it introduces levels of abstraction to identify underlying features and models of existing technologies, as well as integrate stakeholder views represented through cognitive mental models. Third, through the concept of interlocking the perspectives downward the levels, it recognizes the interconnected nature of technologies at an implementation stage and enables the alignment between mental models and current technologies and frameworks. As a tool, the meta-framework serves three main functions: First, it provides insights and knowledge about VEs within existing frameworks. Second, it allows for their comparison. Third, it promotes the reuse of existing components as a groundwork for DT development. By applying the meta-framework to three commonly used DT frameworks, we can extract their single features and models and place them within the context of the VE. This analysis reveals that certain VE representations lack behavioral models, a key concept of DTs. Furthermore, based on an industry-specific use-case, mapping the mental models of specific stakeholders to existing technologies lays the groundwork for new DT solutions. Overall, the presented meta-framework promotes a unified understanding of VEs that is independent of technology and stakeholder specifics.

IEEE AccessVol. 13
TU Wien (AT), University of Applied Sciences Burgenland (AT)
Openalex Percentile: Top 17%
Digital Transformation in Industry
1.24
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