Imagining Data-Objects for Reflective Self-Tracking

Maria Karyda*, Merja Ryöppy, Jacob Buur, Andrés Lucero

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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.
Original languageEnglish
Title of host publicationACM Conference on Human Factors in Computing Systems
Number of pages12
PublisherACM Conference on Human Factors in Computing Systems
Publication date2020
Article number715
ISBN (Electronic)978-1-4503-6708-0/20/04
DOIs
Publication statusPublished - 2020

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Karyda, M., Ryöppy, M., Buur, J., & Lucero, A. (2020). Imagining Data-Objects for Reflective Self-Tracking. In ACM Conference on Human Factors in Computing Systems [715] ACM Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3313831.3376844