Pip Mothersill, Bianca Datta
Objects can communicate a wide range of meanings to us through their form, colours, materials and so on, and can be defined by very numerical functional engineering properties, or much more tactily understood emotive artistic properties. Instead of creating ‘smooth’ forms with a certain surface function or ‘soft’ materials with a specified shore hardness like an engineer might, the designer will search for forms or materials that people perceive as embodying the more complexly emotive feeling of ‘comforting’. Unlike the many databases for scientific material properties, there exists no comprehensive database for these more experiential design properties. In our research we strive to understand and quantify these more emotively communicative aspects of the design properties of objects. The DesignData machine is a first step towards connecting these functional and emotive languages together by collecting data on the more abstract, emotive ways that people perceive and assign meaning to forms and materials. To accomplish this, massive quantities of responses of design samples must be collected in a rapid fashion from a large cross-section of society – a task that would take hundreds of hours if carried out using the more traditional in-person interview methodology. This project tackles this unique challenge of collecting large amounts of qualitative evaluation data on physical samples by providing an automated physical interface to a simple A/B comparison testing.
This machine was conceived by Pip Mothersill as part of her PhD work, and I assisted in fabrication of the initial prototype. As part of my Master's thesis I designed material experiments for this application.