Right. My thoughts are not very clear right now, I’m just trying to get them out of my head. I’m playing around with this idea of semiotics in Information Visualization. There is a common language to what we expect, what the conventions are for creating and representing data as Shneiderman and others have outlined. They aren’t perfect by any means and the lines of distinction are fuzzy. However, I’m wondering a few things.

How do we judge whether or not a visualization is successful? Many visualizations are not easily understood by your average person, like networks. These are hard to read unless one is trained n Information Visualization, but that isn’t the point of this field. The point is to make convoluted data readable in visual form for a particular audience. So, I guess another question is what is readable by your average person? How can complex information be structured or created in a way that they can learn new things or understand the story the visualization/data is telling?

I’m also wondering how high dimensional data is currently represented effectively. I guess it all goes back to the understanding of information visualizations. I keep thinking about Scott McCloud’s Understanding Comics and can’t help but think there should be one for visualizations so more people can read them.  That’s all for now, just loads of questions as I start collecting former work and visualizations.