Here is a sense of what will be happening for the last 4 weeks of class. I am holding to my promise of no exam and no final project. I had also promised that the readings in the class were heavier in the beginning, so we’ll do a little less in the end.
We will have 1 reading assignment per week, each with a discussion. These won’t match the lecture topics exactly, since for some topics I just can’t find good readings. (so that’s 4 more) Some of the readings may have two parts (one for Tuesday, one for Thursday). For some of the readings, there may be extra stuff for 838 students.
We will have 1 seek and find per week (so 4 more). We’ll be a little more explicit about how we evaluate it. (e.g. the thing you find must really be what we’re looking for). People actually seem to like having to find real world examples of things, so we’ll keep the tradition.
There will be another design challenge. Similar to the last one. The exact schedule will be "to be determined."
There will be 2 838 bonus readings (with discussion).
There will probably be a "critique" assignment, where we give you a visualization to write a written critique of.
I had wanted to give an implementation assignment for those who want to try their hands at that. There may be an option to do something implementation oriented instead of some of the regular assignments, with the caveat that it may be more work.
In terms of topics:
Next week (April 13-17) we’ll talk about scalability challenges. We’ll talk about dimensionality reduction, spatial embeddings, and lots of other tricks. We’ll (as in my group) will show off some examples of things we’ve done that try to address these kinds of challenges.
The Following Week April (20-24) we’ll talk about uncertainty visualization, experiments (both using experiments to learning about visualization, but also using visualization to show experimental results). We’ll also talk about visualization system implementation.
The last week of April (27-May1) we’ll talk about 3D and motion.
The last week of class, we’ll try to cram a survey of “standard” scientific visualization (at least the most usual data types, like volumes and vector fields) in. This could have been a whole class unto itself, but for us it will be an after-thought in the end.
