Design insights for more-than-human context-aware self-tracking systems

Snooks, Kim and Richards, Daniel and Lindley, Joseph and Whitham, Roger (2024) Design insights for more-than-human context-aware self-tracking systems. PhD thesis, Lancaster University.

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Abstract

Self-tracking systems collate information about our bodies and present it through metrics about an individual’s health and wellbeing (or their general wellness). As these systems have progressed, they collate data not just about ourselves but those around us, comparing our bodies to multiple other bodies, both human and non-human, including companion animals like cats. A key problem with the current dominant approaches is that they tend to miss out on contextualised information about our general wellness experiences showing a limited, singular perspective of what it means to be healthy and well. Such perspectives can result in harm, by supporting some selves’ experiences over others. In this thesis, it is asked what if self-tracking systems considered different, “more-than-human” perspectives of contextualised general wellness information? Through the introduction of different perspectives of contextualised general wellness information, this thesis aims to understand what it would be like to interact with these perspectives. This involves understanding whether there would be implications with introducing alternative perspectives into self-tracking systems and what this would mean for future self-tracking system design. Using speculative design and design fiction through a ‘Research through Design’ approach, these perspectives are explored to provide design insights for more-than-human context-aware self-tracking systems.

Item Type:
Thesis (PhD)
ID Code:
223651
Deposited By:
Deposited On:
03 Sep 2024 09:35
Refereed?:
No
Published?:
Published
Last Modified:
12 Oct 2024 23:46