Speaker: Liuhuaying Yang (Complexity Science Hub)
Abstract
Complexity science delves into the study of systems with interconnected and interdependent components. Effective communication within this field requires a clear depiction of defined actors and their relationships within a targeted system. While network visualizations are crucial, they represent just one facet of the broader visualization landscape, sometimes falling short in capturing the dynamic nature and emergent behaviors characteristic of complex systems.
To address this limitation, we must incorporate visualizations that highlight indicators and metrics of actors, shedding light on the emergent properties of the system. Additionally, it can also be essential to visualize how these systems evolve over time, capturing the temporal dynamics that influence system behavior. This talk will explore diverse visualization strategies to effectively communicate the intricacies of complex systems, emphasizing the importance of dynamic and metric-focused representations to convey the findings of complexity science studies.
Short bio
Liuhuaying Yang is a data visualization researcher and faculty member at the Complexity Science Hub. She has extensive experience in creating interactive visualizations that bridge academic research with real-world applications. Collaborations with industry, academia, and newsrooms have honed her skills in translating complex data into compelling narratives, earning recognition such as the 2019 TRB Innovations in Transit Performance Measurement Challenge and the World Dataviz Prize 2023.
