Grace Martinez

In Lev Manovich’s essay “The Anti-Sublime Ideal in New Media,” it speaks about the revolutionary role computer technology had on data visualization. It changed the way we look, collect, scale, and display data. Taking what were abstract concepts or big data sets, while drawing on and sometime re-inventing previous mediums of communication.

He compares the modern systematic  abstract art of Mondrian to data visualization in how it is “engaged in a similar reduction as it allows us to see patterns and structures behind the vast and seemingly random data sets. Thus it is possible to think of data visualisation as a new abstraction.” However, he then argues “but if modernist abstraction was in some sense anti-visual – reducing the diversity of familiar, everyday visual experience to highly minimal and redundant structures (again, Mondrian’s art provides a good example) – data visualisation often employs the opposite strategy: the same data set drives endless variations of images (think of various visualisation plug-ins available for music players such as iTunes.) Thus, data visualisation moves from the concrete to the abstract, and then again to the concrete. The quantitative data is reduced to its patterns and structures that are then exploded into many rich and concrete visual images.”

The aim of Data visualization has been to help people understand hard to comprehend concepts and ideas and data, but it’s important to remember that it is a human  interpretation of that data that is behind of all that. It is a human subjective experience and I think the more transparent we can be in our visualizatoins the more truthful and and honest our work will be. Personally, I think it’s important to remember the medium of which we chose to do portray our data visualizations. Which audience can access it? Who can understand it? Who are speaking to? How do the people/subjects we are speaking exist in the mediums we choose? What does it mean to scale very human data to symbols, shapes, and lines?

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