Existing toolkits for data physicalization prioritize ease of use and adoption by novices. This is often achieved by limiting the affordances of the materials used and constraining design possibilities. The result is limited opportunities for creating expressive physicalizations. To address this limitation and to better understand how to support the creation process of expressive physicalizations, we created ClayPhys, a low-fidelity data physicalization toolkit designed to encourage making expressive data physicalizations. Our toolkit consists of clay, clay work tools, instruction and documentation handbooks, and warm-up activities that scaffold the design process. We studied the use of ClayPhys in a one-day workshop with nine expert participants. From our analysis of participants' created data physicalizations, we observed that using ClayPhys, participants could map data to different visual and physical variables, and that their designs incorporated various data interaction styles. Informed by our findings, we discuss implications for designing higher-fidelity expressive data physicalization toolkits.
Bakhtiari et al. (2026) studied this question.