Honorable Mention

A Computational Design Process for Sensing Network Physicalizations

S. Sandra Bae, Takanori Fujiwara, Anders Ynnerman, Ellen Yi-Luen Do, Michael L Rivera, Danielle Albers Szafir

Room: 105

2023-10-25T23:57:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
A sensing network physicalization (N = 20, L = 40). (a) A multi-material 3D printed network physicalization produced by Bae et al’s computational design pipeline. Conductive traces are embedded in the network’s links which enables node selection via capacitive sensing. (b) A computational rendering of the network physicalization showcasing how the conductive traces are distributed throughout the network’s links. The conductive traces use a serpentine pattern.
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Physicalization, tangible interfaces, 3D printing, computational fabrication, design automation, network data


Interaction is critical for data analysis and sensemaking. However, designing interactive physicalizations is challenging as it requires cross-disciplinary knowledge in visualization, fabrication, and electronics. Interactive physicalizations are typically produced in an unstructured manner, resulting in unique solutions for a specific dataset, problem, or interaction that cannot be easily extended or adapted to new scenarios or future physicalizations. To mitigate these challenges, we introduce a computational design pipeline to 3D print network physicalizations with integrated sensing capabilities. Networks are ubiquitous, yet their complex geometry also requires significant engineering considerations to provide intuitive, effective interactions for exploration. Using our pipeline, designers can readily produce network physicalizations supporting selection—the most critical atomic operation for interaction—by touch through capacitive sensing and computational inference. Our computational design pipeline introduces a new design paradigm by concurrently considering the form and interactivity of a physicalization into one cohesive fabrication workflow. We evaluate our approach using (i) computational evaluations, (ii) three usage scenarios focusing on general visualization tasks, and (iii) expert interviews. The design paradigm introduced by our pipeline can lower barriers to physicalization research, creation, and adoption.