Speaker: Daniel Pahr
The growing field of data physicalization holds significant potential for integrating user actions directly into the sensemaking process through physical artifacts. Two promising factors for physical, as opposed to virtual representations, are physical interaction and multimodal perception. Unmediated interaction in the physical space allows users to manipulate and explore data physicalizations in a natural way, harnessing a user’s actions to encode and decode information in a different way than purely virtual representations.
In this dissertation, I explore the incorporation of user action as a means of manipulation and perception into data physicalizations, moving from representations where perception only happens after physical interactions to representations where physical interactions directly stimulate the user’s perception.
I investigate four distinct types of user interactions with data physicalizations and show how each of them can support human perception in different ways. Overall, the results show that even a simple physicalization can highlight the perceptual benefits of physically encoding data by means of natural perception. Abstract representations have to be learned by users but can be supported by physical interactions, while embodied metaphors profit from direct interactivity if the stimulus fits the sensory capabilities.
