Learning from Constraints in Visualizations of Information

Abstract

Visualizations have been part of both humanistic and scientific knowledge production and dissemination for quite a long time. In recent years, however, its use has risen exponentially, fueled in part by the need to extract meaning from huge amounts of information and our inabilities to make sense of data without the aid of external devices. The result is that information visualizations have gained unprecedented prominence and we experience a burgeoning practice of visualizing information in all corners of academia, which includes visual systems and representational tools tailored to humanistic inquiry. It is indisputable that they can and often act as cognitive devices whether aimed at communicating information or for exploration and analyzes of data. Much has been discussed about the benefits offered by visual representations of information. In this talk, I will present the other side of this story and examine several specific constraints imposed on and by visualizations. By means of a series of examples, I will elucidate their capabilities by scrutinizing their limitations. I would like to argue that, though powerful by nature, information visualizations should not serve all research problems uniformly. Ultimately, my goal is to open a conversation about how we can employ information visualizations as research tools in a more critical manner.