Grand Challenges Panel

There is not enough room in this microblog posting for a complete description of that panel – but it was interesting. Georges Grinstein kicked it off by making some good remarks about the nature of Grand Challenges, falsifiable theories, and that you need an idea of the direction in addition to the question. Tamara Munzner gave an excellent presentation (available on her talks page) about outward vs. inward challenges, and presented a few good key criteria (described well on her slides). Daniel Keim criticized her position by saying that she was talking about writing papers not unifying visualization theory, and he's right – still, it's a great start. Keim also went on to talk about how visualization can save the world, and in doing that he picked up Munzner's idea of the "infovis-hard" problem of total political transparency (again, see her slides). Then George Grinstein came back to talk about his ideas for how we can build such a science of visualization, and that's where he lost a good part of the audience. His main idea is to "measure everything," and to use benchmark datasets to drive the development of theory. I don't entirely disagree, but I think some of his comparisons with other fields (like KDD and computer vision) were not 100% applicable. Still, a great panel, and I believe Grinstein can at least make more progress than we have in the last ten years put together. To (roughly) quote him, "we've got enough facts, it's time to build a science!"