| Beschreibung |
Our personal lives are increasingly datafied, with aspects that previously did not exist numerically being counted and used to make predictions on how we can live ”happier, fitter, and better” lives [1]. Using quantification to flatten complex topics, and present them in attractive and easy to read visualizations, these data present themselves as clean, neutral, objective, and standardized.
The results are personal data that lack personality. The data do not reflect us nor how we experienced them. For example, when communicating how sleepy we are, saying ‘I am 5 sleepy’ does not make much sense.
Therefore, this project explores how we can represent data in a more embodied and personal way through dynamic data physicalisations: physical artefacts that represent data through a change in their appearance.
To do so, we will draw on feminist, queer, intersectional, and more-than-human theories. Specifically, we will be looking into autobiographical design and auto-ethnography. Each student will be making their own, personal data physicalisation, live with this artefact, and conduct an auto-ethnographic study during this period.
This project will challenge you to explore what personal data are, how they align and differ from common data perceptions, and how to design for our new perceptions of personal data. Moreover, this project will introduce and give you experience with ”auto-methods” (methods where you are your own user/target group).
This course is suited for students who like to be challenged to find problems, and who enjoy individual work and to come up with their own concepts. Students will focus on research topics such as ”qualitative data representations”, ”data physicalisations”, ”data feminism”, ”showroom research”, ”critical design”, and ”speculative design”. We encourage students to participate that have a high interest in working from theory, coming up with speculative concepts, and learn how to realise those concepts as an artefact. The project is most suited for students who want 18 ECTS.
1. Chris Elsden, Mark Selby, Abigail Durrant, and David Kirk. 2016. Fitter, happier, more productive. Interactions 23, 5: 45–45. https://doi.org/10.1145/2975388
2. Yanni Alexander Loukissas. 2019. All data are local: thinking critically in a data-driven society. MIT Press, London.
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