Enhancing Understanding of Constitutional Law through Visual Design

In this paper, we present a work-in-progress visual analysis prototype to support domain experts in their understanding and analysis of constitutional law. In accordance with digital humanities domain, constitutional data is rich in relational, hierarchical, temporal, and text features. Data have complex implicit network structures and eventbased dynamics and as such they have always posed a challenge to visualization. Through ongoing discussion with experts in constitutional law, we design a prototype with paralleled ThemeRiver and hierarchy tree to support the understanding of constitutional convention data by showing the hierarchical structures and trends of selected attributes through their temporal development, and making values and trends of different attributes comparable simultaneously.

Recommended citation: Yiwen Xing, Nicholas Cole, Rita Borgo, and Alfie Abdul-Rahman. "Enhancing Understanding of Constitutional Law through Visual Design." In IEEE VIS 2021-Posters.
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