One insight illuminated by this and related studies is that in an information world now driven by search, existing art image digitization efforts can have the unintended consequence of (further) skewing perception and understanding of cultural production overall ? in effect, reinforcing either the art historical canon or the de facto (already digitized) canon. That is, at least until more and different images are made available online ? of course the answer is not to stop current digitization efforts, but to enhance them.
This is one more reason that copyright overreach which prevents some images from going online is a bad thing and should be resisted by fair use and better understanding of users? rights in images of copyrighted works. --- On Sun, 9/11/11, Amalyah Keshet [akeshet at imj.org.il] <akeshet at imj.org.il> wrote: From: Amalyah Keshet [akeshet at imj.org.il] <[email protected]> Subject: [MCN-L] FW: cultural analytics To: "'mcn-l at mcn.edu'" <mcn-l at mcn.edu> Date: Sunday, September 11, 2011, 7:26 AM Don't know what to think / do about this, but it's just so cool I have to pass it on. Amalyah Keshet http://www.wolframdatasummit.org/2011/attendee/abstracts/#Manovich ... at the Wolfram Data conference (last week), here's an intriguing presentation: >> >> "How to Compare One Million Images? Visualizing Patterns in Art, >> Games, Comics, Photography, Cinema, Animation, Web, and Print Media >> >> Lev Manovich Professor, University of California, San Diego (UCSD) >> >> The explosive growth of cultural content on the web, including social >> media and the digitization work by museums, libraries, and companies, >> makes possible a fundamentally new paradigm for the study of cultural >> content. We can use computational data analysis and new interactive >> visualization techniques to analyze patterns and trends in massive >> cultural datasets. We call this paradigm cultural analytics. I will >> show examples of visualizations of patterns in cinema, animation, >> video games, magazines, and comics created in our lab >> (softwarestudies.com) at the University of California, San Diego >> (UCSD) and California Institute for Telecommunications and >> Information Technology (Calit2). The presentation will highlight new >> visualization techniques for big data that use next-generalization >> scalable displays such as the HIPerSpace system, which offers 35,840 x 8,000 >> pixels resolution." >> Thanks to Peter Brantley for noticing this. _______________________________________________ You are currently subscribed to mcn-l, the listserv of the Museum Computer Network (http://www.mcn.edu) To post to this list, send messages to: mcn-l at mcn.edu To unsubscribe or change mcn-l delivery options visit: http://toronto.mediatrope.com/mailman/listinfo/mcn-l The MCN-L archives can be found at: http://toronto.mediatrope.com/pipermail/mcn-l/
