IEEE Viz Days 2 and 3
By Linda Fellingham on Oct 31, 2007
Day 2 I went to a workshop on Knowledge-Assisted Visualization. So what the heck does that mean? Mostly it meant using additional a priori information to add to the visualization (which seems kind of obvious) but there was one interesting paper about using statistics of the data to remove the expected (as in the statistical sense) information so the visualization only contains the interesting information. The results looked pretty good. It does seem to me that what is really of interest is visualization-assisted knowledge, but that is a different topic.
Day 3 started off with a keynote address by Rick Stevens of Argonne National Labs on "Visualization Challenges at the Intersection of PetaScale Computing and Biological Sciences". It was an amazing - to me, eye-opening - talk. I've been only peripherally observing the amazing advances in exploring genomes. But I had no idea the complexity of understanding the masses of data that have been uncovered. It is interesting that so much computer power has been applied to getting this information, but not so much to helping to understand it. Stevens showed a great animation that Harvard put together for their biology students ("The Inner Life of the Cell"} that was truly inspiring. I googled it and it can be found at http://www.studiodaily.com/main/searchlist/6850.html.
In the afternoon I went to another "Meet the Scientists" panel. The theme was too much data, inadequate visualization tools, help, help, help. It is really clear that more needs to be invested in visualization infrastructure to keep up with the massive investments in computing that is creating all this data that needs to be analyzed. Scientists want to be able to do interactive visualization to understand and analyze the terabytes (soon petabytes) of data they are continually acquiring. There seems to be a slight mis-match between the many in the vis community thinking that the visualization is the end result, and the scientific community needing visualization to be part of the analysis process.