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Datasets in design ...
Datasets in design research: needs and challenges and the role of AI and GPT in filling the gaps
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- Arjomandi Rad, Mohammad, 1987 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Hajali, Tina, 1996 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Martinsson Bonde, Julian, 1992 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Panarotto, Massimo, 1985 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Wärmefjord, Kristina, 1976 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Malmqvist, Johan, 1964 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Isaksson, Ola, 1969 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- 2024
- 2024
- English.
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In: Proceedings of the Design Society. - 2732-527X. ; 4, s. 1919-1928
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https://doi.org/10.1...
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Abstract
Subject headings
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- Despite the recognized importance of datasets in data-driven design approaches, their extensive study remains limited. We review the current landscape of design datasets and highlight the ongoing need for larger and more comprehensive datasets. Three categories of challenges in dataset development are identified. Analyses show critical dataset gaps in design process where future studies can be directed. Synthetic and end-to-end datasets are suggested as two less explored avenues. The recent application of Generative Pretrained Transformers (GPT) shows their potential in addressing these needs.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)
- HUMANIORA -- Konst -- Design (hsv//swe)
- HUMANITIES -- Arts -- Design (hsv//eng)
Keyword
- artificial intelligence (AI)
- generative design
- data-driven design
- design research
- dataset gap
Publication and Content Type
- kon (subject category)
- ref (subject category)
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