| Beschreibung |
Our personal lives are increasingly becoming datafied, were aspects which previously did not exist numerically are being counted and used to make predictions on how we can live “happier, fitter, and better” lives [1]. Using quantification to simplify complex topics, and present them in attractive and easy to read visualizations, these data present themselves as clean, neutral, and objective—a perfect tool to give us control over our messy everyday lives.
However, these perceptions of data as well as common definitions such as “data are agglomerations of small, discrete signals, represented as 0s and 1s in computer memory” [2], do not match data’s true nature, and how we encounter, live, and experience data in our daily lives. 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 queer data to challenge and resist current personal data norms and practices (such as the Quantified Self). Based on the idea that not all things can be meaningfully quantified, as they are non-fixed, fluid, and interconnected, this project explores how we can re-conceptualize what personal data are, how we track them, and how to represent them. To do so, we will draw on feminist, queer, intersectional, and more-than-human theories. By tracking our own personal data, we will use these theories to speculate about other ways of tracking and representing data (such as data sensification), and develop data artefacts (either a tracking technology or data representation) that borrow from speculative and/or critical design.
Following a Research through Design (RtD) approach, 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.
This course is perfect for students who would like to be challenged to find problems, enjoy individual and (multi-disciplinary) group-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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