Tag Archives: Ben Shneiderman

Ben Shneiderman and Data Visualization

18 Oct

Last Wednesday I attended a talk by Ben Shneiderman at Wellesley.  He mostly spoke about his research in the field of data visualization – basically exploring new ways to present large sets of data.  Not surprisingly, the talk was *very* well attended…I even saw a few professors from the art department which seemed random (or so I thought).

Ben showed a few examples of how powerful alternate methods of visualization can be.  He presented a set of data in tabular form and then showed the same data plotted on a graph.  Immediately obvious was that although the data sets had the same means, the actual functions that described the data were completely different!  It was pretty amazing to be able to find relationships between data points in less than 1 second.

In addition to convincing the audience that data visualization was indeed a powerful tool, Ben let us explore some of his specific projects and tools that he uses to find different patterns.  Ben developed tree maps, which are pretty awesome:

He used these tree maps to show how we can find anomalies and trend in things like stock patterns very quickly.  For example, he showed what the tree map looked like when only one group of companies (for example, the tech industry) is succeeding while others are experiencing a fall in their stock prices.

Along these lines, I really like the idea of taking a nebulous of unstructured data points and producing meaning.  Since I’ve been working on a thesis to create large interactive spaces, I’ve been doing a lot of thinking lately about how I can use very simple sensor data to produce BIG, inspiring results within a space.  I like the idea of having an installation that can leverage a simplistic sensor network and work in conjunction with users to capture and expand upon simple patterns in data.  Much like Ben’s talk, I definitely think the way you choose to present data is directly related to how much attention the data will garner.  For example, if I keep track of traffic patterns in an academic building, I could choose to post a list of statistics on a wall.  Alternately, I could use light and color installations to ambiently highlight areas of high movement.  By exploring more innovative ways of looking at information, we can leverage the kinds of input that humans are naturally attracted to in order to draw attention to interesting occurrences.