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In 2002, Grieves defined the concept of the digital twin as a virtual instance of physical assets capable of continuously mirroring them. Ever since then, driven by remarkable industrial attention, digital twins flourished and ripened in several sectors. The notable industrial adoption has been sided by a growing interest from the software engineering community in general and the software architecture community in particular as demonstrated by the growing number of published peer-reviewed publications and proposed software architectural solutions for digital twins. In this paper, we report on the planning, execution, and results of a systematic mapping study on architecting digital twins. The study captures crucial aspects of software architectures for digital twins as types of architectural solutions, quality attributes, and architectural patterns. It supports practitioners in creating digital twins tailored to their specific needs and researchers in identifying trends and open challenges. Starting from an initial set of potentially relevant 1630 peer-reviewed publications, we selected 140 primary studies. We analysed the set of primary studies using thorough data extraction, analysis, and synthesis process. To compensate for single method limitations and reduce possible threats to conclusion validity, we discussed the results of our study with experts in the software architecture community. Based on our results, the field of software architecture for digital twins is lively and an increasing number of architectural solutions are being proposed. Although there is a lack of widely accepted reference architectural solutions for digital twins, most of them are built using a combination of the layered and service-oriented patterns and address maintainability, performance efficiency, and compatibility quality attributes.

Engineering digital twins following standardised reference architectures is an upcoming requirement for ensuring their adoption and facilitating their creation, processing, and integration. The ISO 23247 standard proposes a reference architecture for digital twins in manufacturing, including an entity-based reference model and a functional view specified in terms of functional entities. During our experience with projects in the field, we noticed that standards, and in particular the ISO 23247 standard, are not completely followed. In this paper, we analyse to what extent digital twin architectures documented in the literature are aligned with the reference architecture presented in the ISO 23247 standard. We achieved this through a mixedmethods research methodology that includes the analysis of 29 digital twin architectures in the manufacturing domain resulting from a systematic literature review of 140 peer-reviewed studies, a survey with 33 respondents, and four semi-structured, in-depth expert interviews. On the basis of our findings, practitioners and researchers can reflect, discuss, and plan actions for future research and development activities.

Digital twins involve the integration of advanced information technologies to create software replicas that control and monitor physical assets. Interoperability is an essential requirement in the engineering of digital twins. This paper is the first study analysing interoperability in digital twin software architectures in the manufacturing industry. We began with an initial set of 2403 peer-reviewed publications and after a screening process, we selected a final set of 21 primary studies. We identified the set of technologies used for data exchange and the level of interoperability achieved during such an exchange. We organised the results according to the ISO 23247 standard and the level of conceptual interoperability model.

The functional suitability of digital twin systems relies on accurately capturing, modelling, and exchanging data from their corresponding assets or processes. Consequently, achieving interoperability among various components and different digital twin systems is crucial. In the current landscape, characterized by various languages supporting diverse semantic models, achieving interoperability is a complex task. Achieving interoperability might involve translating diverse models, either peer-to-peer or through a central pivotal model. In this study, we propose a model-driven engineering approach that leverages higher-order transformations in conjunction with the Asset Administration Shell, acting as the pivotal model to tackle the interoperability challenges associated with digital twin systems. Higher-order transformations are a specific type of model transformation, characterized by their input and/or output being model transformations themselves. Our hypothesis is that such transformations would eliminate the need to manually craft multiple translations toward the Asset Administration Shell. In-stead, a single higher-order transformation would automatically generate these translations. We chose the Asset Administration Shell as our pivotal model, because it is widely recognized as a foundational element for application interoperability in Industry 4.0/5.0. We illustrate our approach through a vehicle use case represented using the Systems Modeling Language version 2 and consolidating this description into an Asset Administration Shell model. Hence, we showcase the applicability and suitability of our proposed approach. To the best of our knowledge, our work represents the first effort to address the translation of Systems Modeling Language version 2 into the Asset Administration Shell.

Digital twins serve as virtual representations of systems, enabling capabilities such as

intelligent monitoring, real-time control, decision-making, and predictive analytics. The

Asset Administration Shell (AAS) is the pivotal Industry 4.0 standard for digital twin

engineering. In parallel, the Systems Modeling Language version 2 (SysMLv2) has

emerged as the main modeling standard for systems engineering, providing a

formalized and semantically rich approach to system modeling. With its growing

adoption, models developed in the early engineering phases are expected to be widely

available in an interchangeable format, encouraging their reuse in digital twins. Instead

of manually re-creating models for digital twinning, existing system models can be

leveraged.

However, SysMLv2 lacks direct integration with digital twin standards such as AAS,

necessitating a dedicated approach for seamless interoperability between the early

engineering phases and the operation of digital twins.

This paper investigates the conceptual alignment between SysMLv2 and AAS

specifications, examines structural and behavioral modeling aspects, and proposes a

systematic approach to mapping SysMLv2 to AAS, ensuring the automatic generation

of AAS models from SysMLv2 models.

To realize this approach, we employ model-driven engineering techniques leveraging

the Eclipse Modeling Framework and model transformations based on the Query View

Transformation language.

The proposed model transformation incorporates query mechanisms for structured

element extraction, information and structural integrity preservation, ensuring semantic

consistency and seamless data integration between the two investigated standards.

We develop and validate the model transformation following an iterative test-driven

development approach using a set of 24 SysMLv2 examples, sourced from the official

SysMLv2 repository.