Visualising dynamic graphs is important for many application areas. For social media networks, they can help us understand the interaction and interests of users online. In biology, they can illustrate the interactions between genes and biological processes. Understanding and designing effective visualisation methods for dynamic network data is fundamental to these areas as well as many others. In this talk, we focus on the effective presentation of dynamic networks. In particular, we summarise recent results on dynamic graph visualisation with respect to animation (presentation of interactive movies of the data), small multiples (presenting the data through several linked windows like a comic book), and drawing stability (the visual stability of the data presentation). We conclude with some recent work on scalable graph visualisation and in the visualisation of sets and their intersections.
Daniel Archambault has been working in the field of information visualization for ten years. His work in this area has focused on the development and evaluation of techniques for visualizing dynamic networks and scalable graph visualizations. His research has been been applied to many areas outside of computer science, including the digital humanities, biology, networking, sociology, and social media analysis.