The lack of formalization in domain-specific language (DSL) specification often results in proprietary solutions, inconsistent semantics, and hinders interdisciplinary collaboration—especially when artifacts are exchanged across lifecycle phases involving diverse stakeholders. To address this, we propose an ontology-based DSL specification process that improves semantic consistency, is tool-independent, and supports reuse beyond model-based environments. Our earlier work focused on metamodel-based formalization, but remains tied to modeling tools and is therefore limited to MBSE contexts. Ontologies, in contrast, are implementation-independent and can serve as a semantic foundation for both modeling and non-modeling artifacts. Exemplified on using the Automotive Reference Architecture Model (ARAM) DSL, we created a domain ontology based on a widely accepted methodology, which we adapted and evaluated for this context. We delineate the roles of ontology and metamodel in the language specification process and position this work as the next step in a top-down effort toward a formalized, lifecycle-spanning DSL engineering approach.

Graphical domain-specific languages (DSLs) often result in tool-specific, non-reusable implementations due to the lack of standardized specification for their visual (concrete) syntax. This paper presents the MOF-based Profile Generator (MOPRO), a prototype that transforms a formally specified metamodel into a UML Profile implementation, enabling direct use of the DSL in the modeling tool Enterprise Architect. The specification builds on our previous work, which extended the MOF standard with a machine-readable definition of the concrete syntax model (CSM), but had not yet demonstrated its practical interpretability. MOPRO addresses this gap and is evaluated using a security DSL that shares structural similarities with the RAMI 4.0 Toolbox—whose evolution has required time-consuming manual DSL updates. The results confirm that a single standardized specification is sufficient to automate DSL implementation. While currently tailored to Enterprise Architect, the transformation process is adaptable to other tools, providing a foundation for reusable, consistent, and less error-prone DSL development across platforms.

Rising complexity in the automotive domain and its interrelations with other domains as the power systems demand a domain-specific modeling framework to facilitate the development of complex vehicular systems and support interdisciplinary and cross-domain communication. Inspired by the Smart Grid Architecture Model (SGAM) framework, which addresses similar challenges in the smart grid domain, the Automotive Reference Architecture Model (ARAM) framework was developed for the automotive domain. This framework provides interoperability with the smart grid domain and enables a transition from analysis to architectural model levels by being compatible with the Software Platform Embedded Systems (SPES) methodology. This compatibility enables a structured development approach following domain-specific systems engineering (DSSE). However, the last published work towards an evolution of ARAM left some issues unaddressed. With this paper, we aim to complete previous work-in-progress efforts and introduce the latest evolution of the ARAM framework. Incorporating industry feedback and insights from case studies, we present a newly developed domain-specific language (DSL) and the accompanying modeling tool, the ARAM Toolbox. To demonstrate these artifacts we developed a case study. With this work we therefore lay the groundwork for future advancements in model-based systems engineering within the automotive sector, providing a basis for further research into interdisciplinary and cross-domain collaboration.

Due to the rising complexity in the automotive domain a suitable modeling framework to facilitate development as well as interdisciplinary communication is needed. In the domain of smart grids, the Smart Grid Architecture Model (SGAM) framework turned out to be a suitable tool for coping with complexity whilst providing cross-disciplinary understanding. A similar approach exists for the automotive domain: the Automotive Reference Architecture Model (ARAM) framework. As opposed to other automotive frameworks, this one offers interoperability with the smart grid framework, which simplifies cross-domain collaboration. During the development of ARAM, the Software Platform Embedded Systems (SPES) methodology gained momentum. This methodology can be considered an architectural model while the automotive framework can be considered an analysis model, according to the domain-specific systems engineering approach. In order to follow this approach, a transformation between the two models must be possible. This work-in-progress paper aims at presenting first approaches of an adapted version of the ARAM framework, proposing a reworked structure that is compatible with both, SGAM and SPES.

The fourth industrial revolution resulted in the emergence of new ways for engineering production lines with the goal to optimize manufacturing processes by reducing expenses at the same time. This trend is mainly supported by the application of interconnected components, which are managed in a distributed way, as impelled by the Industrial Internet of Things (IIoT) or Cyber-physical Systems (CPS). While the complexity of these Systems of Systems (SoSs) is constantly rising, requirements engineering before actual implementing the system becomes increasingly difficult. Thus, comprehensive frameworks providing a foundation for model-based systems engineering, like the Reference Architecture Model Industrie 4.0 (RAMI 4.0) or the Software Platform Embedded Systems (SPES), have been introduced. Although providing a standardized methodology, missing formalizations impede the modeling of systems according to detailed architectural specifications. To address these issues, this paper introduces an approach for eliciting, specifying and managing requirements according to a particular process and aligned to architectural standards. In the end, the result is evaluated by a real-world case study. The outcome of this work will either verify the future system to develop by ensuring traceability or enable interoperability by dealing as a consistent reference point across viewpoints, systems or even domains.