cultural analytics: to be continued

I spent last weekend at a workshop on ‘visual methods in cultural studies’, hosted by the Department of Urban Culture and the Institute of Cultural Studies at the Adam Mickiewicza University in Poznan, Poland.  It was interesting, and I got lots of pointers from Polish colleagues who approach cultural studies from the humanities rather than the social sciences.  One of them is the Software Studies Initiative site, hosted by Lev Manovich and oriented to/from the digital humanities.

It discusses what Manovich calls ‘cultural analytics’: working with big datasets (of images, in his case), to show differences in a dataset both visually and spatially.  As well as some theoretical discussion pieces (one of which claims that scholars no longer have to choose between depth and breadth in their methodology), there’s lots of hands-on advice for doing this sort of analytics, and even a software package to download and play with called ImagePlot.  (When did it become trendy for one-word titles to have two capital letters?)

a visualisation of a million black and white manga pages

Having got over my embarassment at not already knowing about this site, I immediately thought about using this package to analyse the digital visualisations that my current research project is examining.  These are visualisations of an urban redevelopment project currently under construction in Doha, Qatar.  There are probably millions of these visualisations, if you take into account all the different versions of every image made as the project has evolved since its initial design work in 2008.  Wouldn’t it be great, I thought, to run these through ImagePlot and get some sort of visual description of the lot: the colours, the tones, the hues, the saturation.  This would be interesting because a lot of effort and discussion seems to have gone on about getting these aspects of the images ‘right’: right in terms of accurately reflecting the light in Doha but also in terms of conveying the right sort of ‘atmosphere’ for the development.  ImagePlot would presumably allow us to show these colour qualities directly.

But even if cultural analytics makes the possibility of such an analysis real, there are still difficulties.  In this case, the database itself.  I don’t have access to all those images and I’m not sure I ever would because they are scattered across hundreds of servers and hard drives in the offices of architects, visualisers and developers.  So there still seems to be a crucial issue for big data analytics about access to data; and about the (dare I say it) representativeness of the data that you can get your hands on.

I look forward to delving deeper into the Software Studies Initiative site to learn more about this and – I’m sure – many other aspects of visual cultural analytics.