Miguel PdL

While compiling my last entry on the map of science it did make me think that in this day and age data visualisation in the ICT world should be more interactive, like this visualisation of the Linux kernel.
What caught my eye was this work by Tony Hirst on visualising the lap time data from Australian F1 grand-prix in 2009 using ManyEyes, which has led onto some very interesting social commentary on the visualisation of UK MP’s expenses.
But is all these cases of visualisation research an after the fact activity with steady data sets and results.

But I wonder can macro architectural network patterns married with micro network component specifications and fused in a data visualisation tool, be a way to address future Internet design, pre-deployment?
And to make this happen, what exact “steady” data would I need to realise such a wonder?

I’ve always had an interest in data visualisation, one of my most viewed blog entries is on a data visualisation of the relationships between different scientific disciplines, which is currently framed and hanging on my home office wall (the only one!), so this recently published map of a journal network that outlines the relationships between various scientific domains has had me interested again.
This time the data visualisation is based on the collection

of nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institute’s Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains ….

and is full recorded in a paper by Johan Bollen, Herbert Van de Sompel, Aric Hagberg, Luis Bettencourt, Ryan Chute, Marko A. Rodriguez, Lyudmila Balakireva, “Clickstream Data Yields High-Resolution Maps of Science”
What results is a map that

represents the structure of scholarly activity from an observational perspective, not from a prescriptive or motivational one. User interactions with scholarly web portals are shaped by many constraints, including citation links, search engine results, and user interface features. In this paper we do not attempt to explain or motivate these interactions, but merely to demonstrate how their overall structure can be charted and described from clickstream maps of science.

The PLoS site related to this paper has some interesting comments and the related article from the NY Times: Map of Knowledge offers some further insight from the authors.