Abstract
The current work elaborates upon a Generative Data Exploration method, which is a design technique aiming at supporting designers in integrating data in their design activities. Digital data offers new opportunities in all sort of professional domains, yet existing approaches and tools to manipulate data are predominantly targeted at data experts. As access to data is becoming democratised, new types of techniques are needed to leverage the agency of designers and to empower them to utilise data in the design process. Designers without prior data experience can benefit from the techniques, know-how, best practices of experts, if such expert knowledge is codified in design methods and tools. The aims of a Generative Data Exploration method are two-fold. First, the method facilitates a learning curve on gaining holistic data literacy. Second, the method supports designing where digital data, exploration of data and sense-making of data is part of the process.
Keywords
design methods; data exploration; generative design; fuzzy front-end
DOI
https://doi.org/10.21606/drs.2018.565
Citation
Kun, P., Mulder, I., and Kortuem, G. (2018) Data Exploration for Generative Design Research, in Storni, C., Leahy, K., McMahon, M., Lloyd, P. and Bohemia, E. (eds.), Design as a catalyst for change - DRS International Conference 2018, 25-28 June, Limerick, Ireland. https://doi.org/10.21606/drs.2018.565
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Data Exploration for Generative Design Research
The current work elaborates upon a Generative Data Exploration method, which is a design technique aiming at supporting designers in integrating data in their design activities. Digital data offers new opportunities in all sort of professional domains, yet existing approaches and tools to manipulate data are predominantly targeted at data experts. As access to data is becoming democratised, new types of techniques are needed to leverage the agency of designers and to empower them to utilise data in the design process. Designers without prior data experience can benefit from the techniques, know-how, best practices of experts, if such expert knowledge is codified in design methods and tools. The aims of a Generative Data Exploration method are two-fold. First, the method facilitates a learning curve on gaining holistic data literacy. Second, the method supports designing where digital data, exploration of data and sense-making of data is part of the process.