This study proposes a mapping of a core ontology for missions and capabilities in Systems of Systems to a foundational ontology. It gives a brief overview of the core ontology, compares various foundation ontologies, outlines suitability characteristics, and maps the two ontologies. The mapping process is based on a superclasssubclass mapping. To ensure that the mapping is to the highest level of granularity, this process goes beyond the selected foundation ontology and includes extensions provided by common core ontologies. The outcome of the mapping provides insights into the richness of ontology realism, the connectedness of concepts and ontologies, the consistency this mapping adds to systems engineering efforts by supporting the methodological approach of Model-Based Systems Engineering, and the necessity of conformance in ontological research and implementation. This mapping supports the alignment in knowledge representation by explicitly highlighting the kind of expected input of each core ontology concept. © 2026, Science and Technology Publications, Lda. All rights reserved.

Digital twins, dynamic digital representations of physical systems, are emerging as transformative tools for enhancing crisis preparedness and resilience in critical societal sectors. By enabling real-time monitoring, simulation, and optimization, these technologies offer actionable insights to support proactive risk mitigation, efficient resource allocation, and continuous improvement of crisis response strategies. This study provides a comprehensive knowledge overview of digital twins, focusing on their applicability and impact in key sectors such as energy, healthcare, and transportation. Specifically, it examines the essential services most suited for digital twin adoption, the role of safety-critical data throughout their life-cycle, and their utility in identifying and mitigating risks within critical infrastructure. We employed a mixed-methods research design, combining systematic and gray literature reviews with expert interviews to integrate academic insights with practical perspectives. The findings reveal significant opportunities for digital twins to enhance operational efficiency, strategic planning, and crisis management. However, practical implementation remains in its infancy, with challenges related to cost, complexity, and limited real-world applications. In addition, this study provides actionable recommendations for stakeholders, emphasizing investment in digital twin technologies, robust data governance, and the development of standardized protocols. Future research directions include exploring applications of DTs in emerging sectors, such as crisis preparedness and societal resilience, advancing artificial intelligence integration, and adopting a system-of-systems perspective to address societal challenges comprehensively.

Abstract Software engineering is decision intensive. Evidence‐based software engineering is suggested for decision‐making concerning the use of methods and technologies when developing software. Software development often includes the reuse of software assets, for example, open‐source components. Which components to use have implications on the quality of the software (e.g., maintainability). Thus, research is needed to support decision‐making for composite software. This paper presents a roadmap for research required to support evidence‐based decision‐making for choosing and integrating assets in composite software systems. The roadmap is developed as an output from a 5‐year project in the area, including researchers from three different organizations. The roadmap is developed in an iterative process and is based on (1) systematic literature reviews of the area; (2) investigations of the state of practice, including a case survey and a survey; and (3) development and evaluation of solutions for asset identification and selection. The research activities resulted in identifying 11 areas in need of research. The areas are grouped into two categories: areas enabling evidence‐based decision‐making and those related to supporting the decision‐making. The roadmap outlines research needs in these 11 areas. The research challenges and research directions presented in this roadmap are key areas for further research to support evidence‐based decision‐making for composite software.

The choice of which software component to use influences the success of a software system. Only a few empirical studies investigate how the choice of components is conducted in industrial practice. This is important to understand to tailor research solutions to the needs of the industry. Existing studies focus on the choice for off-the-shelf (OTS) components. It is, however, also important to understand the implications of the choice of alternative component sourcing options (CSOs), such as outsourcing versus the use of OTS. Previous research has shown that the choice has major implications on the development process as well as on the ability to evolve the system. The objective of this study is to explore how decision making took place in industry to choose among CSOs. Overall, 22 industrial cases have been studied through a case survey. The results show that the solutions specifically for CSO decisions are deterministic and based on optimization approaches. The non-deterministic solutions proposed for architectural group decision making appear to suit the CSO decision making in industry better. Interestingly, the final decision was perceived negatively in nine cases and positively in seven cases, while in the remaining cases it was perceived as neither positive nor negative.

This paper introduces a decision canvas for capturing architecture decisions in software and systems engineering. The canvas leverages a dedicated taxonomy, denoted GRADE, meant for establishing the basics of the vocabulary for assessing and choosing architectural assets in the development of software-intensive systems. The canvas serves as a template for practitioners to discuss and document architecture decisions, i.e., capture, understand and communicate decisions among decision-makers and to others. It also serves as a way to reflect on past decision-making activities devoted to both tentative and concluding decisions in the development of software-intensive systems. The canvas has been assessed by means of preliminary internal and external evaluations with four scenarios. The results are promising as the canvas fulfills its intended objectives while satisfying most of the needs of the subjects participating in the evaluation.

Vehicle platooning has been studied for several decades, with objectives such as improved traffic throughput on existing infrastructure or reduced energy consumption. All the time, it has been apparent that safety is an important issue. However, there are no comprehensive analyses of what is needed to achieve safety in platooning, but only scattered pieces of information. This paper investigates, through a systematic literature review, what is known about safety for platooning, including what analysis methods have been used, what hazards and failures have been identified, and solution elements that have been proposed to improve safety. Based on this, a gap analysis is performed to identify outstanding questions that need to be addressed in future research. These include dealing with a business ecosystem of actors that cooperate and compete around platooning, refining safety analysis methods to make them suitable for systems-of-systems, dealing with variability in vehicles, and finding solutions to various human factors issues.

The automotive industry has recently agreed upon the embedded software standard AUTOSAR, which structures an application into reusable components that can be deployed using a configuration scheme. However, this configuration takes place at design time, with no provision for dynamically installing components to reconfigure the system. In this paper, we present the design and implementation of a dynamic component model that extends AUTOSAR with the possibility to add plug-in components at runtime. This opens up for shorter deployment time for new functions; opportunities for vehicles to participate in federated embedded systems; and involvement of third-party software developers.

A Quarry and Aggregate production site consist of sequential production processes and activities to process and produce the output products. Compared to a fixed manufacturing plant, the quarry processes involve mobile machines such as wheel loaders, trucks and articulated haulers and a highly dynamic road infrastructure. Today, the mobile machines are generally not synchronized or controlled towards the overall throughput of the site in real time. This indicates a general improvement potential in increased productivity at quarry sites, but also unsolved challenges for the same reason. Assuming a wireless control system that controls speed and throughput of the different processes and activities, there would be a fuel reduction potential in controlling the mobile machines. This optimization requires models of machine fuel consumption for different applications, velocities and travel times. The main contribution of this paper is the presentation of fuel measurements based on different speeds, site application characteristics and travel times for hauling operation. The fuel measures reveal important aspects regarding how different velocities impact fuel consumption. The results of fuel measurements show a potential in fuel savings of up to 42% and a typical improvement of 20–30% depending on machine speeds, travel times, application and site characteristics. Based on this, some of the applications and challenges in wirelessly controlling machines are discussed.

Traditionally, Embedded Systems (ES) are tightly linked to physical products, and closed both for communication to the surrounding world and to additions or modifications by third parties. New technical solutions are however emerging that allow addition of plug-in software, as well as external communication for both software installation and data exchange. These mechanisms in combination will allow for the construction of Federated Embedded Systems (FES). Expected benefits include the possibility of third-party actors developing add-on functionality; a shorter time to market for new functions; and the ability to upgrade existing products in the field. This will however require not only new technical solutions, but also a transformation of the software ecosystems for ES. This paper aims at providing an initial characterization of the mechanisms that need to be present to make a FES ecosystem successful. This includes identification of the actors, the possible business models, the effects on product development processes, methods and tools, as well as on the product architecture. The research was carried out as an explorative case study based on interviews with 15 senior staff members at 9 companies related to ES that represent different roles in a future ecosystem for FES. The interview data was analyzed and the findings were mapped according to the Business Model Canvas (BMC). The findings from the study describe the main characteristics of a FES ecosystem, and identify the challenges for future research and practice. The case study indicates that new actors exist in the FES ecosystem compared to a traditional supply chain, and that their roles and relations are redefined. The business models include new revenue streams and services, but also create the need for trade-offs between, e.g., openness and dependability in the architecture, as well as new ways of working.

Embedded automotive architectures and software need to support a large number of vehicle product lines over many years of production. This leads to a complexity and many uncertain factors when developing such systems and a need for support in the design process. An evaluation method using real options provides the opportunity to analyze the cost of designing for flexibility to cope with a future growth of a product line, based on the estimated value of the future functionality. In this paper real options is applied on a case within the automotive industry. To improve the usability an evaluation process is defined to aid engineers. This process provides a way of valuing system designs and enables the engineer to think about the future in a systematic manor. The value of a flexible design can thereby be quantified and the proposed process shows how it can be accepted by practitioners.

In the early phases of embedded real-time systems development, design decisions are made with large consequences on the quality of the resulting product. At the same time, only limited information is available about key attributes, which makes it difficult to get correct decisions. In this paper, it is studied how to include uncertainty in the information in early phases and to handle the risks involved. Using Monte Carlo simulation, the uncertainties are evaluated based on estimations of basic parameters. The technique is applied to schedulability analysis, and it is shown that the results can be counter-intuitive, and thus that current design practice can lead to higher risk than assumed by the designers.

This paper compares different scheduling policies applied to distributed systems intended for automotive real-time control applications. We describe the characteristics of systems using fixed priority (FP) and static cyclic (SC) scheduling of processors and bus communication, with combinations ranging from FP bus-FP processors to SC bus-SC processors. FP bus is represented by the Controller Area Network protocol (CAN) and SC bus by a Time Division Multiple Access (TDMA) protocol. We also study the effects of using a global time base. Our main concern is control performance, including input and output jitter and control delay and therefore the response time of a sequence of control tasks and the related communication. For each system configuration we analyze the expected response times of a series of control related tasks (delay) and the temporal variation of the input and output instants (jitter).

The automotive industry has been late in introducing object oriented (OO) analysis, design, and programming, compared to many other businesses. This is partly due to the fact that OO programming has been considered too expensive in terms of computational resources, but also because there are elements in the application functions for which OO methods do not give sufficient support. Nevertheless, OO techniques provide many advantages, and we discuss how they can be used for automotive real time control applications. The suggested approach is holistic in the following respects: it treats functionality on the vehicle level rather than on individual control units; it includes both the embedded system and its environment; and it considers both hardware and software.

The process of designing many industrial products is today characterized by the use of ad hoc methods, iterative trial and error-like proceedings and the engineer's own experience and intuition. This is due to the complexity of the problems attempted, and the difficulty to formalize them and express them mathematically. The authors suggest the use of a genetic algorithm to partially automate industrial design, and describe an example where the method has been successfully used to improve the design of a gas turbine.