Imagining Data-Objects for Reflective Self-Tracking

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Abstract

While self-tracking data is typically captured real-time in a lived experience, the data is often stored in a manner detached from the context where it belongs. Research has shown that there is a potential to enhance people's lived experiences with data-objects (artifacts representing contextually relevant data), for individual and collective reflections through a physical portrayal of data. This paper expands that research by studying how to design contextually relevant data-objects based on people's needs. We conducted a participatory research project with five households using object theater as a core method to encourage participants to speculate upon combinations of meaningful objects and personal data archives. In this paper, we detail three aspects that seem relevant for designing data-objects: social sharing, contextual ambiguity and interaction with the body. We show how an experience-centric view on data-objects can contribute with the contextual, social and bodily interplay between people, data and objects.

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Karyda, M., Ryöppy, M., Buur, J., & Lucero, A. (2020). Imagining Data-Objects for Reflective Self-Tracking. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3313831.3376844

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