I spent a lot of time last weekend watching the weather radar on TV. Friday night was my first Big Southern Storm, and let me just say: I’ll take a good ‘ol northern blizzard any day.
Anyway.
During a break in the storm, I was struck by how complicated a modern TV weather map is. You’ve got all those colors to take in and synthesize, geographic references to match them up with, a time scale, spinning refresh line, and sometimes even wind speeds or other situational data. Yet somehow everybody can take it in. You never hear anybody complain about the weather map being too complex.
I think the success is due to a combination of familiarity and a highly visual representation. After you see enough local maps of any kind, you get an idea of what towns are placed where. Once you gain that sense of location, the town names become almost unnecessary to even read. Then the colors: again, no reading necessary. Red bad. Green not so bad. That’s about the extent of knowledge required.
So if this kind of visual representation of highly complex data can be so successful, why can’t the new crop of visual search engines?
EBSCO recently added the feature to their databases, and I’m not really impressed. Sure it looks slick, but I just can’t be nearly as efficient with their expanding connected bubbles as I can in traditional searches.
Perhaps I haven’t given myself time to gain that critical threshold of familiarity. But I’d love to try some sort of visual search system based on a weather map’s amorphous blobs and see how it compares. Maybe the years of honing that system can be drawn upon.