|statement // mary flanagan // john klima // lisa jevbratt // rethinking the visual // event|
jevbratt // mapping transitions proposal
The project I propose for “Rethinking the Visual: New Technologies in the Context of Society and Culture” is a software which generates visualizations of the movement of crawlers over the Web and the data that the crawlers collect from the Web. It is a development of aspects of the software that I wrote for “Mapping the Web Infome” (http://dma.sjsu.edu/jevbratt/lifelike/). I want to explore some specific ideas I have in relation to visualization that came up as I was working on the project. The original software allowed a selected group of artists to create crawlers to harvest information from the web and to make visualizations of the information for the audience to experience. This software will allow the audience itself to set the parameters for the crawling activity and the visualization methods and it will provide a more developed tool for visualizing the information.
The user sets parameters for the crawler and the visualizations in a Web interface. The software allows the user to manipulate the crawler’s behavior in several ways. The user decides where it should begin crawling; it could for example start on a Web page specified by the user, or on a page resulting from an automatic search using a search engine, or on a random Web. Another set of options is determining how the crawler should “move around”. i. e. the order in which links are followed; for example it could be following all links on all pages sequentially or “dancing around” in a defined pattern. The crawler can be set to visit a page once or every time it encounters a link to it. The data resulting from many revisits will have repetitions talking about the structure of the sites, revealing its topology, while data resulting from single visits will generate larger amount of different data. The crawler stops when a certain condition is met as determined by the user, for example after a certain amount of time, when a specific site or a specific piece of information is found. When the crawler is done and the visualization is created, the user is automatically notified by e-mail. The crawler could run for several hours.
Some of the ideas on visualization that will be explored in developing the visualization tools:
Complex systems, visualizations and the Sublime:
Jack Burnham wrote in the article ‘System Aestetics’ in 1969 about the advantage of aesthetic decision making in complex systems (economical, cultural, technical etc). He argues that the aesthetic decision is the only possible way of making decisions because we can’t grasp all the details of the complexity in order to make “rational” decisions, we just have to be awed by it and make an intuitive decision.
The idea relates to the German romantic philosopher Emmanuel Kant's idea of the sublime. He claims that when we face large amounts of information, huge distances and ungraspable sizes our senses mobilized and we get scared but excited and empowered. Kant distinguishes between two distinct aesthetic pleasures:
Beauty: aesthetic pleasure derived from the small graspable things we feel we can understand.
Sublimity: experiences of fear and fascination of “endlessness”, of quantities and spaces so large that we feel we can not grasp them. Kant claims that in experiencing the sublime our senses and our organizing abilities are mobilized, and, contrary to what could be believed, we feel empowered.
Many strategies for aiding people in the task of finding information on the web or the task of turning any large set of data into knowledge assumes that people should be presented less information, less choices in order to be able to make sense out of the data. However, humans are capable of sorting through enormous amounts of information and make sensible and complex decisions in a split second. The ability of driving a car could be a good example. Supported by the ideas of Burham and Kant I propose that when presented with a lot of data, people are forced to make more intuitive decisions. The scale shift in taking millions of web sites and present ten of them on one page is a problem.
A common mistake in visualization is to compress the information too much, to decrease the amount of information through calculations, embodying inexplicit assumptions that are never explained. The compression rate is too high, there is too much information left out for the ‘image’ to be meaningful. We need a more high-resolution ‘image’ to be able to make an intuitive selection within it. The problem with a lot of visualizations are not too much information but too little. People always seek the highest point to get an overview, to be able to make decisions on where to go. One important task of visualizations is not to produce specific views of a data environment but the lookout points in those environments. The visualization should provide the means to make an aesthetic decision.
Visualizations should tell us something we did not know about the data. Much visualization is merely illustrations of models we already conceived of. Data is being plugged into a structure that in it self holds all beliefs that can be derived from the imagery. The data is used to decorate our models.
Visualizations should be realistic in that they have a direct correlation to the reality it is mapping. Yet, visualizations are not representations of a reality, they are reality, and in that sense they are minimalist. They should be objects for interpretation, not interpretations. They should be experienced, not talk about experience. The reason for this approach is twofold. On a more basic level it allows the image teach us something about the data, it allow us to use our vision to think. On another level it makes the visualizations function as art in more interesting ways. Connecting them in various ways to artistic traditions from pre-modern art such as cave paintings to abstract expressionism and minimalism to post-structuralist deconstructions of power structures embedded in data. It allows visualizations to ”… create metaphors that alludes to meaning but do not denote meaning. By saying precisely what they mean as imprecisely as possible” (Jamake Highwater about the creation of art in “Language of Vision, Meditations on Myth and Metaphor”)
The aesthetic that follows from this thinking is very “plain”. It is strict and limited in order to not impose its structure on its possible interpretations and meanings.
Generalized visualization strategies:
One aim is to come closer to a generalized visualization method - a method or a set of methods that can be used on data of very different kinds. One problem in this approach is demarcation, where does a ‘data unit’ start and end? We find a good example of this problem in the attempts to detect genes in DNA.