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DEVELOPING SYSTEMS VISUALISATIONS IN DESIGN THROUGH A TYPOLOGY OF VISUAL TASKS: A MECHATRONIC CASE

Published online by Cambridge University Press:  27 July 2021

Agzam Idrissov*
Affiliation:
DTU - Technical University of Denmark
Simon Rapp
Affiliation:
KIT - Karlsruhe Institute of Technology
Albert Albers
Affiliation:
KIT - Karlsruhe Institute of Technology
Anja M. Maier
Affiliation:
DTU - Technical University of Denmark
*
Idrissov, Agzam, DTU - Technical University of Denmark, Engineering Systems Group, Denmark, agzid@dtu.dk

Abstract

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Visual representations are essential to design. Data-rich representations such as systems visualisations are gaining prominence in engineering practice. However, as such visualisations are often developed ad-hoc, we propose more systematically to link visual tasks with design-specific tasks for which the visualisations are used. Whereas research on such linking focuses mostly on CAD models and sketches, no such studies are yet available for systems visualisations. Thus, this paper introduces a typology of visual tasks from the Information Visualisation field to aid the development of systems visualisations in design. To build a visualisation using the typology, a case study with engineering students developing an autonomous robot was conducted. Through interviews and analysis of product representations used, design-specific tasks were identified and decomposed into visual tasks. Then, a visualisation that assisted the team in performing their design activities was created. Results illustrate the benefits of using such a typology to describe visual tasks and generate systems visualisations. The study suggests implications for researchers studying visual representations in design as well as for developers of systems visualisations.

Type
Article
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), 2021. Published by Cambridge University Press

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