Ben Shneiderman, a professor at the University of Maryland’s Human-Computer Interaction Lab and author of Leonardo’s Laptop, gave a talk at Ryerson University yesterday and at the University of Toronto today, on two different topics:
At Ryerson he talked about creativity support tools. I was a bit frustrated by his approach to the topic: the creativity segment of the talk was inconclusive, and although Shneiderman stressed the importance of careful empirical case studies to evaluate tools (with which I fully agree), he never really described them nor the way his team addressed the challenges of doing good empirical work in the area.
The talk at the University of Toronto, on visualization of high dimensional information (which I talked about last week) was more satisfying. The visualization tools Shneiderman presented (mostly the same ones as in Ryerson, but with more time -or so I felt) are really, really appealing – very polished in comparison to most academic prototypes. I’ll cover them in future posts, but if you want a glimpse, you can check the already famous Treemaps (with applications in the stock market) and the Hierarchical Clustering Explorer, which is way more impressive than this link suggests.
The demos were fun, but since they took most of the talk’s time there was not a lot of room to discuss the principles behind them. Shneiderman didn’t really explain the theory that supports the tools, the criteria used to evaluate their effectiveness, nor the limits of these approaches. I actually got the feeling that the tools were built at least partially on a hunch, not on an information visualization theory, and that there isn’t an articulated theory behind some of them, but I might be wrong. I’ll expand on this when I learn more.
Wouldn’t you agree that all academic research starts with a hunch, and then being justified after-the-fact with a theory and/or empirical evident?
🙂
It’s perfectly OK for academic research to start with a hunch –what’s wrong is to *stop* there!