An Ontological Context Modeling Framework for Coping with the Dynamic Contexts of Cyber-physical Systems

Brings, Jennifer; Daun, Marian; Hildebrandt, Constantin; Törsleff, Sebastian

doi:10.5220/0006603403960403

Cited by 8 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 1 summarizes the different notions of “context” proposed in the literature and juxtaposes the relationship to our work. In the following, we derive guiding principles by relating these central notions of “context” to observations from the CPS literature 57 . These guiding principles serve as the basis for the context modeling framework which we will describe in Section 3.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Particularly for CPS, functional collaboration can be understood as a “common force” that binds functional concerns together (see Harper and Zheng, 57 p. 124). A common way to handle common concerns is the adoption of views onto the interacting systems 66 …”

Section: Background and Related Workmentioning

confidence: 99%

“…In the following, we derive guiding principles by relating these central notions of "context" to observations from the CPS literature. 57 These guiding principles serve as the basis for the context modeling framework which we will describe in Section 3.…”

Section: Towards a Context Theory For Cyber-physical Systemsmentioning

confidence: 99%

See 2 more Smart Citations

Context modeling for cyber‐physical systems

Daun

Tenbergen

2022

J Software Evolu Process

View full text Add to dashboard Cite

When developing cyber-physical systems (CPS), the context is of vital importance.CPS interact with the world not only through sensing the environment and acting upon it (like embedded systems) but also by communicating with other CPS (like systems in the Internet of Things [IoT]). This means that the context interactions CPS must deal with are much greater than regular embedded or IoT systems: On the one hand, external systems and human users constrain the specific interaction among them. On the other hand, properties of these external systems, human users, and laws, regulations, or standards constrain the way the CPS must be developed. In this paper, we propose a comprehensive, ontologically grounded context modeling framework to systematically explore the problem space in which a CPS under development will operate. This allows for the systematic elicitation of requirements for the CPS, early validation and verification of its properties, and safety assessment of its context interactions at runtime.

show abstract

Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Context modeling for cyber‐physical systems

Daun

Tenbergen

2022

J Software Evolu Process

View full text Add to dashboard Cite

show abstract

“…The ontologies also enable such collaborative CPS to perform context-related reasoning and exchange context-related information. Furthermore, Daun et al (2016) and Brings et al (2018) proposes a context ontology to cope with highly dynamic contexts of CPS by explicitly differentiating between not only the system and its context but also between the CPS network the system participates in, as well as the system network's context. They use the ontology to keep the different contexts of multiple CPS consistent with one other and the super system's specifications.…”

Section: C5 Cpsmentioning

confidence: 99%

Ontology Learning for Systems Engineering Body of Knowledge

Yang

Cormican

2021

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

“…In general, the context of a system consists of all objects that are relevant to the system, but cannot be influenced by developers and is perceived as given [18]. Context objects (COs) can be divided into two different types [19]: Collaborative context objects and non-collaborative context objects. A collaborative context object is able to share information about itself in a reactive or proactive manner with the SUC; for example, the SUC calls a self-description service, or a collaborative context object pro-actively sends a selfdescription to the SUC or other CESs in a CSG, while accessing a network.…”

Section: Information Exchange In Csgsmentioning

confidence: 99%

EURECA: epistemic uncertainty classification scheme for runtime information exchange in collaborative system groups

Hildebrandt

Bandyszak

Petrovska

et al. 2019

SICS Softw.-Inensiv. Cyber-Phys. Syst.

Self Cite

View full text Add to dashboard Cite

Collaborative Embedded Systems (CES) typically operate in highly dynamic contexts that cannot be completely predicted during design time. These systems are subject to a wide range of uncertainties occurring at runtime, which can be distinguished in aleatory or epistemic. While aleatory uncertainty refers to stochasticity that is present in natural or physical processes and systems, epistemic uncertainty refers to the knowledge that is available to the system, for example, in the form of an ontology, being insufficient for the functionalities that require certain knowledge. Even though both of these two kinds of uncertainties are relevant for CES, epistemic uncertainties are especially important, since forming Collaborative System Groups (CSGs) requires a structured exchange of information. In the au

show abstract

An Ontological Context Modeling Framework for Coping with the Dynamic Contexts of Cyber-physical Systems

Cited by 8 publications

References 0 publications

Context modeling for cyber‐physical systems

Context modeling for cyber‐physical systems

Ontology Learning for Systems Engineering Body of Knowledge

EURECA: epistemic uncertainty classification scheme for runtime information exchange in collaborative system groups

Contact Info

Product

Resources

About