I really liked Hadley Wickham’s tutorial on using R and ggplot2.
You don’t need R programming skills to analyse datasets with ggplot2 and come up with charts
like these, although it doesn’t hurt.
It was nice to see Vadim Ogievetsky demo protovis the way it should be used.
Incidentally, protovis 3.3, which includes animation, is about to be released. Protovis for java is
This was the day on the workshop where I spoke. There were other sessions on storytelling,
such as this remarkable paper from Edward Segel and Jeff Heer.
My favorite session of that day was Lars Grammel’s talk on how
information visualization novices construct visualizations . This charts show the various barriers
that they encounter.
The presentation of (again) Had Wickham on graphical inference in infovis presents an
interesting idea. Can an impartial viewer tell the difference between one data representation,
and that of several similar, but generated datasets? If many such viewers can tell apart the
original representation, then it is significantly different from the others. (see also this)
This paper by Danyel Fisher shows how advanced visualizations (such as those made with
processing, protovis, flash or this here bing map) can be brought into Excel, using data from the
workbooks – the best of both worlds, often represented very far apart from each other.