Datasets in design research: needs and challenges and the role of AI and GPT in filling the gaps
Paper i proceeding, 2024

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.

artificial intelligence (AI)

generative design

data-driven design

design research

dataset gap

Författare

Mohammad Arjomandi Rad

Chalmers, Industri- och materialvetenskap, Produktutveckling

Tina Hajali

Chalmers, Industri- och materialvetenskap, Produktutveckling

Julian Martinsson Bonde

Chalmers, Industri- och materialvetenskap, Produktutveckling

Massimo Panarotto

Chalmers, Industri- och materialvetenskap, Produktutveckling

Kristina Wärmefjord

Chalmers, Industri- och materialvetenskap, Produktutveckling

Johan Malmqvist

Chalmers, Industri- och materialvetenskap, Produktutveckling

Ola Isaksson

Chalmers, Industri- och materialvetenskap, Produktutveckling

Proceedings of the Design Society

2732527X (eISSN)

Vol. 4 1919-1928

2024 International Design Society Conference, Design 2024
Cavtat, Dubrovnik, Croatia,

Ämneskategorier

Produktionsteknik, arbetsvetenskap och ergonomi

Design

DOI

10.1017/pds.2024.194

Mer information

Senast uppdaterat

2024-08-06