Tasks and Ontologies in Engineering Modelling

J.L. Top, Jan Top, J.M. Akkermans, Hans Akkermans

Research output: Contribution to journalArticleAcademic

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Abstract

Constructing models of physical systems is a recurring activity in engineering problem solving. This paper presents a generic knowledge-level analysis of the task of engineering modelling. Starting from the premise that modelling is a design-like activity, it proposes the Specify-Construct-Assess (SCA) problem-solving method for decomposition of the modelling task. A second structuring principle is found in the distinction between and separation of different ontological viewpoints. Here, we introduce three engineering ontologies that have their own specific roles and methods in the modelling task: functional components, physical processes, mathematical constraints. The combination of the proposed task and ontology decompositions leads to a particular approach to modelling that we call evolutionary modelling. This approach is supported by a knowledge-based system called QuBA. The implications of evolutionary modelling for structuring the modelling process, the content of produced models, as well as for the organization of reusable model fragment libraries are discussed.
Original languageUndefined
Pages (from-to)-
JournalInternational journal of human-computer studies
Volume41
Issue number4
DOIs
Publication statusPublished - 1994

Keywords

  • METIS-118747
  • IR-18227

Cite this

Top, J.L. ; Top, Jan ; Akkermans, J.M. ; Akkermans, Hans. / Tasks and Ontologies in Engineering Modelling. In: International journal of human-computer studies. 1994 ; Vol. 41, No. 4. pp. -.
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Tasks and Ontologies in Engineering Modelling. / Top, J.L.; Top, Jan; Akkermans, J.M.; Akkermans, Hans.

In: International journal of human-computer studies, Vol. 41, No. 4, 1994, p. -.

Research output: Contribution to journalArticleAcademic

TY - JOUR

T1 - Tasks and Ontologies in Engineering Modelling

AU - Top, J.L.

AU - Top, Jan

AU - Akkermans, J.M.

AU - Akkermans, Hans

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N2 - Constructing models of physical systems is a recurring activity in engineering problem solving. This paper presents a generic knowledge-level analysis of the task of engineering modelling. Starting from the premise that modelling is a design-like activity, it proposes the Specify-Construct-Assess (SCA) problem-solving method for decomposition of the modelling task. A second structuring principle is found in the distinction between and separation of different ontological viewpoints. Here, we introduce three engineering ontologies that have their own specific roles and methods in the modelling task: functional components, physical processes, mathematical constraints. The combination of the proposed task and ontology decompositions leads to a particular approach to modelling that we call evolutionary modelling. This approach is supported by a knowledge-based system called QuBA. The implications of evolutionary modelling for structuring the modelling process, the content of produced models, as well as for the organization of reusable model fragment libraries are discussed.

AB - Constructing models of physical systems is a recurring activity in engineering problem solving. This paper presents a generic knowledge-level analysis of the task of engineering modelling. Starting from the premise that modelling is a design-like activity, it proposes the Specify-Construct-Assess (SCA) problem-solving method for decomposition of the modelling task. A second structuring principle is found in the distinction between and separation of different ontological viewpoints. Here, we introduce three engineering ontologies that have their own specific roles and methods in the modelling task: functional components, physical processes, mathematical constraints. The combination of the proposed task and ontology decompositions leads to a particular approach to modelling that we call evolutionary modelling. This approach is supported by a knowledge-based system called QuBA. The implications of evolutionary modelling for structuring the modelling process, the content of produced models, as well as for the organization of reusable model fragment libraries are discussed.

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