Bahare Bakhtiari

Topic

Designing Expressive Data Physicalizations through Craft-Based Techniques and Tools

Department of Computer Science

Date & location

• Wednesday, July 15, 2026

• 8:00 P.M.

• Virtual Defence

Reviewers

Supervisory Committee

• Dr. Charles Perin, Department of Computer Science, University of Victoria (Co-Supervisor)

• Dr. Sowmya Somanath, Department of Computer Science, UVic (Co-Supervisor)

• Dr. Aurélien Tabard, LIRIS, Université Claude Bernard Lyon 1 (Outside Member) 

External Examiner

• Dr. Clement Zheng, Division of Industrial Design, National University of Singapore 

Chair of Oral Examination

• Dr. Ardeshir Shojaeinasab, Department of Electrical and Computer Engineering, UVic

   

Abstract

Casual data visualization is an approach that emphasizes the personal, subjective, and expressive aspects of data. While most data visualization tools supporting ca sual visualization rely on 2D screens, data physicalization–representing data through properties of the physical environment and materials–has offered the opportunity to engage different sensory modalities.

However, many current data physicalization examples rely heavily on variables common to data visualizations and don’t fully leverage the broader design space of physical variables and embodied interactions. To address this gap, I investigated craft techniques as a means of supporting expressive data representations by expanding the range of variables and interaction possibilities.

In this thesis, I gained first-hand experience in craft-based data physicalization using a Research-through-Design (RtD) process. Additionally, I conducted a workshop study with visualization and design experts to gain insights into the opportunities and challenges of using craft to support expressive data physicalization. I focused on textile- and clay-based crafts, as these materials are among the most-explored craft domains in HCI, yet remain underexplored for data representation.

I investigated how to design activities that support expressive data physicalizations and introduced the FlexPhys cookbook to guide researchers in designing such activities. Collectively, across the above methodologies, I demonstrated how the affordances of craft techniques can support diverse physical variables and interactions. These findings contribute to how craft techniques support the expansion of the ex pressive data physicalization design space. Additionally, I found tensions around slowness, consistency, and the learning curve in using craft techniques in data physicalizations. I proposed implications for designing computational and educational interventions to support expressive data physicalizations through craft techniques.