In search of

Media Theorist Lev Manovichs todays post on his blog asks for new methods to deal with the huge amounts of visual material online. The title of the post “Against search” is of course a pun on Susan Sontags essay “Against interpretation”. It was noted for her critique on the dominance of hermeneutics in art criticism back in the 60s. For Manvich, photo-sharing sites, a well as media archives, of today lack the possibility for discovery. For one, you are always first confronted with a search engine, so you need to have some idea of what you are looking for. And second, online databases are some kind of a black box, because you never see all content at once. He writes:

“The popular social science method for working with larger media sets in an objective manner – content analysis, i.e. tagging of semantics in a media collection by several people using a predefined vocabulary of terms also requires that a researcher decide before hand what information would be relevant to tag.

Unfortunately, the current standard in media access – computer search – does not take us out of this paradigm. Search interface is a blank frame waiting for you to type something. Before you click on search button, you have to decide what keywords and phrases to search for. So while the search brings a dramatic increase in speed of access, it assumes is that you know beforehand something about the collection worth exploring further.”

I felt just the same in my research about online image collections or archives, especially with those, which cover a specific topic. Playing around with the features is hard, when you are not familiar with the terminology and don’t know with what term to start the query. Nevertheless, the search engine is currently the ultimate tool, our gateway to information.

We had never been before confronted with such a mass of data, with humans producing more images thanks to accessible cameras and easy digital publishing, which are administered by machines. So the more data is produced the more we are dependant on the work of machines doing this work for us.

It is an interesting observation that there is a tendency to go from qualitative to quantitative research, which goes along with the advent of digital image collections. Thanks to the „memory“ and simple automated analysis methods like find, match, and compare, a lot of material can be overviewed. This makes it possible to draw new connections and relationships. At least, this is what many wish for. I wonder, is it the pure presence of all data that make us to look for patterns within all data:

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Ryan Trecartin: Any Ever


One of my currently favorite artists is exhibiting at PS1; the show is on until September so I very much hope I am going to be able to be in New York.
Since I don’t find the time at the moment to write a longer piece on him, I thought I gather some voices about his work.


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