  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.
