Survey on Ontology Languages

Kalibatiene, Diana; Vasilecas, Olegas

doi:10.1007/978-3-642-24511-4_10

Cited by 46 publications

(27 citation statements)

References 18 publications

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“…Current standards include languages such as the Web Ontology Language (OWL) and the Resource Description Language (RDF). OWL is based on RDF, but with the advantages of being better equipped for description logics and constraints checking [24]. An ontology made in OWL is composed of individuals, classes and their properties, which together are used to describe concepts of the intended domain modelled in the ontology.…”

Section: Capability-and System-of-systems Engineeringmentioning

confidence: 99%

An Ontological Approach to System of Systems Engineering in Product Development

Franzén¹,

Staack²,

Jouannet³

et al. 2019

Proceedings of the 10th Aerospace Technology Congress, October 8-9, 2019, Stockholm, Sweden

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This paper presents an approach to system-of-systems engineering for product development with the use of ontology. A proposed method for building as well as using ontology to generate and explore system-of-systems design spaces based on identified system-of-system needs is presented. The method is largely built to cover the first levels of related work, where a process for system of systems in the context of product development is introduced. Within this work, it is shown that scenarios for a system-of-systems can be used to identify needs and subsequently the system-of-systems capabilities that fulfils them. The allocation of capabilities to possible constituent systems is used to show the available design space. The proposed method of this paper therefore addresses these initial challenges and provides a framework for approaching the system-of-systems design space creation using ontology. A case study is used to test the method on a fictitious search and rescue scenario based on available resources and information from the Swedish Maritime Administration. The case study shows that a representation of a system-of-systems scenario can be created in an ontology using the method. The ontology provides a representation of the involved entities from the fictitious scenario and their existing relationships. Defined ontology classes containing conditions are used to represent the identified needs for the system-of-systems. The invocation of a description logic reasoner is subsequently used to classify and create an inferred ontology where the available system-of-systems solutions are represented as sub-classes and individuals of the defined classes representing the needs. Finally, several classes representing different possible system-of-systems needs are used to explore the available design space and to identify the most persistent solutions of the case study.

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Section: Capability-and System-of-systems Engineeringmentioning

confidence: 99%

An Ontological Approach to System of Systems Engineering in Product Development

Franzén¹,

Staack²,

Jouannet³

et al. 2019

Proceedings of the 10th Aerospace Technology Congress, October 8-9, 2019, Stockholm, Sweden

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show abstract

“…Recently, the design and implementation of ontologies has been intensified for industrial applications [44]. There are many options for designing and implementing ontologies [45], such as the Ontology Web Language (OWL) [46], which is a based on the RDF (https://www.w3.org/RDF/). In any case, the syntax and semantics of ontological models are the key characteristics that make them understandable by both humans and machines.…”

Section: Knowledge Based Systemsmentioning

confidence: 99%

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

et al. 2018

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The employment of tools and techniques for monitoring and supervising the performance of industrial systems has become essential for enterprises that seek to be more competitive in today’s market. The main reason is the need for validating tasks that are executed by systems, such as industrial machines, which are involved in production processes. The early detection of malfunctions and/or improvable system values permits the anticipation to critical issues that may delay or even disallow productivity. Advances on Information and Communication Technologies (ICT)-based technologies allows the collection of data on system runtime. In fact, the data is not only collected but formatted and integrated in computer nodes. Then, the formatted data can be further processed and analyzed. This article focuses on the utilization of standard Key Performance Indicators (KPIs), which are a set of parameters that permit the evaluation of the performance of systems. More precisely, the presented research work demonstrates the implementation and visualization of a set of KPIs defined in the ISO 22400 standard-Automation systems and integration, for manufacturing operations management. The approach is validated within a discrete manufacturing web-based interface that is currently used for monitoring and controlling an assembly line at runtime. The selected ISO 22400 KPIs are described within an ontology, which the description is done according to the data models included in the KPI Markup Language (KPIML), which is an XML implementation developed by the Manufacturing Enterprise Solutions Association (MESA) international organization.

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“…Based on this reduced gap between ontologies and modeling, we look at whether ontology languages are suitable for our application scenario. Although there are several languages available [22], we focus on the Web Ontology Lanugage (OWL) as it is the most popular and best supported language.…”

Section: Ontology Languagesmentioning

confidence: 99%

Variability Modeling of Cryptographic Components

Nadi

Krüger

2016

Proceedings of the Tenth International Workshop on Variability Modelling of Software-Intensive Systems

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Software systems need to use cryptography to protect any sensitive data they collect. However, there are various classes of cryptographic components (e.g., ciphers, digests, etc.), each suitable for a specific purpose. Additionally, each class of such components comes with various algorithms and configurations. Finding the right combination of algorithms and correct settings to use is often difficult. We believe that using variability modeling to model these algorithms, their relationships, and restrictions can help non-experts navigate this complex domain. In this paper, we report on our experience modeling cryptographic components in Clafer, a modeling language that combines feature modeling and metamodeling. We discuss design decisions we took as well as the challenges we ran into. Our work helps expand variability modeling into new domains and sheds lights on modeling requirements that appear in practice.

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Survey on Ontology Languages

Cited by 46 publications

References 18 publications

An Ontological Approach to System of Systems Engineering in Product Development

An Ontological Approach to System of Systems Engineering in Product Development

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

Variability Modeling of Cryptographic Components

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