digital, noise, utopian matters

Wednesday, October 21, 2009

Utopias ~ how to dream them? How to build them? | Pool

Utopias ~ how to dream them? How to build them? | Pool

Although this link/title is to Nigel Heyller's new project, the title resonated with a day I just spent up at the University of Otago listening to presentations about eResearch. yup. Electronic research is something new, big, fast and its coming our way! It means we will be able to collaborate in ways only hiterto imagined, huge scale multi-media lectures will occur, (PhD's may even include images) research will become open, and we, well, we will share stuff. What was so disturbingly utopian about the vison presented was not only that the day felt it had already passed, but that the very subject of study was never engaged. What exactly are we going to do with these "fat pipes" that can now access the multi-power of supercomputers? Here the by-line becomes important - how to dream them? how to build them?
I went along to the eResearch day because Zita has sugested that we potentially access the KAREN network to form our contribution ot the electrosmog festival next March. And yes KAREN is there; it is fast, and currently only 0.2% of it is being used. The faciliators (the company who own KAREN) REANNZ want us to use it, but can't quite come up with 'how'. The scientists are doing a good job. KAREN allows people to share vast amounts of data, they can run simulations, the earth can shake in real time as models are trialled. The same goes for the historians, eResaerch allows them to share vast databases of information. The realisation dawned on me ... science and history can share the supercomputer because they both deal with data. But where does this leave the data-light disciplines of art? Do we have any need for supercomputing and access to vast bandwidth? And what if the very topics we want to study themselves are digital? Do we feed the digital data down the digital data tube? and what does it look like when it comes out the other end?
Science in this model is about sight. If we can see it we will understand more. If we can grasp at a data-set from over here and mix it with one from over there, we will be able to see something new. The visualisations proved the point. The historians shared the same approach. If we can overlay the demographic information of pre-revolutionary Paris with a database of music and images, we will know something we didn't previously.
The problem comes in the generation of the data, and the reliance on repeatability. Data is not static unless we make it be. Data is always selective, as are our methods. This vast coming together of resources and information (which is not the same as data) means that the way knowledge is constructed is changing. And this was certianly acknowledged. But what was not acknowledged was that our methods need to change too. Images are not simply there to illustrate. Images contribute knowledge. They are not there to be picked apart for historical fact, they are there because an artist has made a particular series of decisions about how best to do what it is they do - visually. And more often than not has streatched the 'truth' along the way.
eResearch in the academy does not yet seem to engage digital materials as materials for study, but as material sthrough which study occurs.
There is something that art (and more particularly the methods of art history) can contribute to this vision, and it is a wealth of content and analysis that say don't trust the utopian agenda, epecially when it is driven by a technology based on scale.

KAREN network: http://www.karen.net.nz/home/
eResearch: http://extreme.otago.ac.nz/ocs/index.php/eResearch/er09
history and networked digital media: http://southseas.nla.gov.au/