Improving Conceptual Modeling with Object-Process Methodology Stereotypes

Kohen, Hanan; Dori, Dov

doi:10.3390/app11052301

Cited by 7 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Munich Agile MBSE Concept (MAGIC) adopted agile into MBSE for requirement traceability, better communication among stakeholders, achieving design automation, and iterative and incremental development [55]. For conceptual modeling of IoT systems, issues with stereotype aspects of Object-Process Methodology (OPM) ISO 19450 are studied [56]. Naqvi et al investigated the use of Protégé to design test strategies for IoT systems using an ontological reasoning approach [57] while MATTER is introduced for model-based generation of executable test scripts for IoT systems [58].…”

Section: A Integration With Business and Management Methodologiesmentioning

confidence: 99%

Model-Based System Engineering of the Internet of Things: A Bibliometric Literature Analysis

Ahmad

2023

IEEE Access

View full text Add to dashboard Cite

Model-based System Engineering (MBSE) of the Internet of Things (IoT) literature is broad, and analysis of this literature enables the identification of themes and potential future study topics that will influence system development. This paper reports on bibliometric literature analysis of MBSE of IoT. It considers conference and journal publication trends in the state-of-the-art to identify emerging research themes from the standpoint of trans/multi-disciplinary scholarship and technology. We used Elsevier's Scopus database to find relevant publications from January 2018 to December 2022. Using publication citation ranking and other factors (e.g., publication venues), we selected 110 articles and then analyzed them using BibExcel and VOSviewer software tools. With a modest decline in 2021, this analysis shows an overall increase in publications during the time period. A thematic analysis of the abstracts revealed a strong focus on the introduction of reference architectures and integration of MBSE with business and management methodologies like Agile and BPMN 2.0. Model-driven engineering and machine learning techniques are essential among the enablers for realization of complex heterogeneous IoT systems in the realm of Industry 4.0. We highlight these findings to better understand and meet the enduring challenge of scaling MBSE of IoT across diverse sectors like health, manufacturing, and transportation.INDEX TERMS BibExcel, bibliometrics, Internet of Things, industry 4.0, model-based system engineering, model-driven engineering, thematic analysis, VOSviewer.

show abstract

Section: A Integration With Business and Management Methodologiesmentioning

confidence: 99%

Model-Based System Engineering of the Internet of Things: A Bibliometric Literature Analysis

Ahmad

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Introducing stereotypes has led many modelers to misuse them, particularly in places where domain-level modeling would be a better fit [17]. In most cases, the equivalent of UML stereotypes could be accomplished by means of OPM constructs that render stereotypes unnecessary, but modeling requirements emerging from such developments as the proliferation of IoT have raised the need to introduce a robust stereotyping mechanism into OPM [18].…”

Section: Opm Stereotypesmentioning

confidence: 99%

Securing the Internet of Things with Object-Process Methodology Stereotypes

Kohen¹,

Dori²

2022

Preprint

Self Cite

View full text Add to dashboard Cite

<p>The Internet of Things (IoT) is creating a network of cyber-physical devices – sensors, actuators, and other devices, which monitor and control physical systems, such as manufacturing facilities operating with the Industry 4.0 paradigm, while collecting and sharing massive data globally over the internet. As the IoT security landscape evolves, so does the “cyber mafia,” which targets cyber-physical systems from the corporate level all the way to Industry 4.0 floor-shop control systems, in which IoT is a key component. IoT devices are becoming ubiquitous and controllable from hand-held devices, raising the potential to disrupt or destroy large industrial complexes in a touch of a screen if not protected properly. This growing risk mandates the adoption of new approaches to incorporating rigorous security standards into IoT systems as early as possible in their system lifecycle. A methodology is presented for incorporating into IoT systems security as a bona fide, quantifiable attribute that is built into the components (objects) and operations (processes). To this end, the synergy of combining model-based systems engineering with embedded IoT system security is leveraged. At the heart of the methodology is a combined qualitative-quantitative IoT OPM model of the system with security scores, which provides for evaluating underlying system configurations, each with its level of security and possibly other optimization criteria. This approach enables balancing IoT systems’ metrics, such as performance and cost, with security, and even optimizing the system under specified constraints.</p>

show abstract

Developing Industry 4 Systems with OPM ISO 19450 Augmented with MAXIM

Dori

2022

Handbook of Model-Based Systems Engineering

View full text Add to dashboard Cite

Improving Conceptual Modeling with Object-Process Methodology Stereotypes

Cited by 7 publications

References 35 publications

Model-Based System Engineering of the Internet of Things: A Bibliometric Literature Analysis

Model-Based System Engineering of the Internet of Things: A Bibliometric Literature Analysis

Securing the Internet of Things with Object-Process Methodology Stereotypes

Developing Industry 4 Systems with OPM ISO 19450 Augmented with MAXIM

Contact Info

Product

Resources

About