Qualitative Design Support for Engineering and Architecture

Abstract

Conventional design support software tools cannot effectively manage the complex, heterogeneous information used in engineering and architecture (EA) tasks. Crucially, despite uncertainty being an inherent quality of EA information particularly in the early stages of a design project, current tools solely rely on numerical approaches which do not support such incomplete and vague information. In this paper, we establish a complete framework for developing qualitative support tools that directly address these shortcomings. Our framework is application oriented and addresses the broader issues surrounding the actual use of qualitative methods. It provides design principles and strategies that allow a software engineer to develop custom qualitative software tools according to their specific EA task specifications. Our framework also provides the engineer with practical theory and guidelines for implementing their custom qualitative model and validating their system using context specific test data. We demonstrate the validity of our framework by presenting a case study in architectural lighting in which a prototype qualitative reasoning engine successfully automates qualitative logic about the subjective impressions of a lighting installation.