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MODELLING THE DESIGN OF MODELS: AN EXAMPLE USING CRISP-DM

Published online by Cambridge University Press:  19 June 2023

Udo Kannengiesser  and
John S. Gero
Udo Kannengiesser*
Affiliation:
Johannes Kepler University Linz;
John S. Gero
Affiliation:
University of North Carolina at Charlotte, USA
*
Kannengiesser, Udo, Johannes Kepler University Linz, Austria, udo.kannengiesser@jku.at

Abstract

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Design is widely understood as a domain-independent notion, comprising any activity concerned with creating artefacts. This paper shows that models can be viewed as artefacts, and that the design of models resembles the design of artefacts in other domains. The function-behaviour-structure (FBS) ontology of design is applied to models, mapping generic characteristics of models derived from literature on modelling onto basic, design-ontological categories. An example of model design, namely the CRISP-DM model for designing data mining models, is analysed and compared with models of designing in other domains (systems engineering, mechanical engineering, software engineering, and service design). The results show that there are fundamental commonalities but also differences, revealing the need for further research in developing a theory of model design.

Keywords

Design theoryProduct modelling / modelsOntologiesDesign methodologyModel design

Information

Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 2705 - 2714
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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