ABSTRACT / Communicating complexity science results can be as challenging as conducting a novel research. Data visualization became an effective way for presenting results, but sometimes charts and diagrams are simply not enough, especially when targeting a broader audience. What are the (other) possible ways to present complex data or abstract models? What are the challenges and solutions in reducing research debt and increasing accessibility? In this talk, multiple visualization projects from Complexity Science Hub will be showcased for these questions.
BIO / Liuhuaying Yang is a data visualization researcher at Complexity Science Hub. Her expertise is in design and front-end development of interactive data visualizations on the interface of academic research and applications. She has worked with the MIT Senseable City Lab and SMART FM in Singapore as a data visualization specialist and SPH Lianhe Zaobao in Singapore as a data visualization designer for interactive data journalism projects. Beside an interest in efficient ways to use data visualization to communicate complex topics, she believes in using an artistic and humanistic approach to engage wide audiences.