Just been playing with generating tag clouds, based on the UCAS keywords which I obtained before Christmas. These are now integrated into the view of programmes, but perhaps all such relationships are worth reversing - here keyword to programme - and the obvious way to do this is with a tag cloud. Ian reminds me of my play with Postscript, generating exam result lists in fonts scaled to the mark itself. The big plus here was that when students were sorted into ascending order of the overall average, you could see at a glance how well each separate exam correlated with the overall.
My tag cloud uses xquery and xslt. First pass to compute the tags and counts, then compute min and max counts from this computed element, and a scaling factor, all in Xquery. XSLT generates the cloud, computing a fontsize based on the count. All a bit slow but it does the job.
I've also just realised a feature of most clouds I've seen - double description [Bateson]. That is tags are not only scaled in size but intensity is increased as well. Newzingo uses a 7 point scale, not the continuous variation I'd assumed from my Postscript days, where both font size and red intensity increase together. Clouds differ in the link styles - default isnt appropriate since it's just a page of links, but just what style is best? I've set the title attribute on my tags, containing the course codes themselves for a quick check but this seems to conflict with hover styling.
But I wonder how to use the comparative idea here - so that keywords in one faculty can be contrasted with those in another, in order to visualise the difference between the two faculties. Perhaps the trick would be a single map which can be dynamicly switched between the two - perhaps even programmed to do so, like a flicker star-map comparator. I would need to get the two maps to register, so that there is a single merged map, but words can be turned on or off - perhaps I'd have to drop the size scaling since this will alter the position of text. Just coluring the text by coding for the datasets and varying the intensity proportional to importance.
Since our new VC seems likely to be merging faculties, this might be a useful tool for him to see which ones to merge - quelle horreur - its just the way this visualisation might be used!