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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. 

Data physicalization has emerged as a new method to represent and interact with data physically rather than digitally. Physical representations afford visual analysis in comparable ways to traditional, desktop- based visualization by introducing new capabilities, such as facilitating tactile manipulation, accessible interactions, and immersion, that are beyond traditional 2D visualizations. However, physicalization has historically been a niche aspect of visualization research due to its unique challenges. This work discusses the current challenges and highlights three areas where data physicalization can aid existing research thrusts: broadening participation, supporting analytics, and promoting creative expression.