Data-Painting: Expressive Free-Form Visualisation

Miriam Sturdee, Søren Knudsen, Sheelagh Carpendale

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review


Data visualization can be powerful in enabling us to make sense of complex data. Expressive data representation – where individuals have control over the nature of the output – is hard to incorporate into existing frameworks and techniques for visualization. The power of informal, rough, expressive sketches in working out ideas is well documented. This points to an opportunity to better understand how expressivity can exist in data visualization creation. We explore the expressive potential of Data Painting through a study aimed at improving our understanding of what people need and make use of in creating novel examples of data expression. Participants use exact measures of paint for data-mapping and then explore the expressive possibilities of free-form data representation. Our intentions are to improve our understanding of expressivity in data visualization; to raise questions as to the creation and use of non-traditional data visualizations; and to suggest directions for expressivity in visualization.
TitelProceedings of DRS2022
StatusUdgivet - 2022


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