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Data-inspired co-design for museum and gallery visitor experiences

Darzentas, Dimitrios; Cameron, Harriet; Wagner, Hanne; Craigon, Peter; Bodiaj, Edgar; Spence, Jocelyn; Tennent, Paul; Benford, Steve


Harriet Cameron

Hanne Wagner

Peter Craigon

Edgar Bodiaj

Jocelyn Spence

Paul Tennent

Steve Benford


The capture and analysis of diverse data is widely recognized as being vital to the design of new products and services across the digital economy. We focus on its use to inspire the co-design of visitor experiences in museums as a distinctive case that reveals opportunities and challenges for the use of personal data. We present a portfolio of data-inspired visiting experiences that emerged from a 3-year Research Through Design process. These include the overlay of virtual models on physical exhibits, a smartphone app for creating personalized tours as gifts, visualizations of emotional responses to exhibits, and the data-driven use of ideation cards. We reflect across our portfolio to articulate the diverse ways in which data can inspire design through the use of ambiguity, visualization, and inter-personalization; how data inspire co-design through the process of co-ideation, co-creation, and co-interpretation; and how its use must negotiate the challenges of privacy, ownership, and transparency. By adopting a human perspective on data, we are able to chart out the complex and rich information that can inform design activities and contribute to datasets that can drive creativity support systems.

Journal Article Type Article
Acceptance Date Oct 5, 2021
Online Publication Date Feb 9, 2022
Publication Date 2022
Deposit Date Feb 14, 2022
Publicly Available Date Feb 14, 2022
Journal Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Print ISSN 0890-0604
Electronic ISSN 1469-1760
Publisher Cambridge University Press
Peer Reviewed Peer Reviewed
Volume 36
Public URL


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