Speaker
Description
Scientific simulations or data acquisition processes often result in large amounts of data samples that need to be "connected" to allow people to understand the information/meaning hidden within. However, if we simply connect all related data points we may end up with an even larger dataset that is more difficult to understand. I will thus talk about illustrative forms of visualization that are inspired by a long tradition of hand-made illustration. In particular, I will talk about the concept of abstraction, using examples from brain connectivity visualization and from structural biology. I will talk about different forms of abstraction, photometric and geometric abstraction, and show how they can be used to create meaningful illustrative visualizations of scientific datasets.
