Weekly Head Voices #12: Ceci n’est pas une bibliothèque.

Welcome to the latest edition of the Weekly Head Voices, in which I briefly touch upon the, to my mind, mention-worthy events that took place within my field of observation during week 5 of the year 2010, and with which I too finally have an excuse to (ab)use the famous words of Magritte for my dubious ends. :)

WE INTERRUPT THIS PROGRAMME FOR THE FOLLOWING IMPORTANT ANNOUNCEMENT:

I’m officially not supposed to talk about this until the next edition of the Weekly Head Voices, but it’s too big and too cool to keep quiet about until then.  Google has just released Buzz, their location-based status / media updating system, and it’s fantastically cool.  I’ve just posted my first Buzz via Google Maps 4.0 on my E71 (I think I’m the third buzz in Delft EVAR).  Don’t know what Buzz is? Check this YouTube clip:

YOU WILL NOW BE RETURNED TO YOUR NORMAL PROGRAMMING.

The reason for the title of this post is my Saturday visit to DOK, Delft’s unique library concept. It’s not really a library, but more of a fantastic place of gathering that coincidentally contains thousands of books, CDs, DVDs and, err, a coffee shop! They even have a number of sonic chairs that one can make use of to listen to music via the mounted Macs. This Saturday, live music by one of the artists who exhibited at the DOK.  I made you a short snippet:

As even this short edition should end on a philosophical note, I’d like to conclude with an interesting discussion I had on whether the type of research we do in (medical) visualisation can be considered to be science. Very strictly speaking, the scientific method consists of observation, hypothesis forming and finally experimentation to prove or disprove the hypothesis. A large body of visualisation work is concerned with making stuff that solves hard problems, i.e. formulative research as opposed to the more traditional evaluative research. Although the question of whether making stuff that solves hard problems constitutes science is a complex discussion that deserves a whole year of blog posts, I am going to conclude with one possible and simple take on situation:

By taking this constructive approach we are, besides actually solving problems (a neat by-product, no?), discovering how to create effective visual representations of complex phenomena hidden in even more complex data. By doing this, we are in fact observing the supremely complex system consisting of the whole pipeline from data acquisition to insight, all the while experimenting with parameters (in the widest possible sense of the world) and thus confirming or disproving hypotheses concerning the nature of the pipeline and its various components. Together, these hypotheses make up the model that governs the effective extraction of insight from data via the human visual system.

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