Computational Visualization for Critical Thinking

This paper looks back at historical precedents for how computational systems and ideas have been visualized as a means of access to and engagement with a broader audience, and to develop a new more tangible language to address abstraction. These precedents share a subversive ground in using a visual language to provoke new ways of engaging with about complex ideas. Two new approaches to visualizing algorithmic systems are proposed for the emerging context of algorithmic ethics in society, looking at prototypical algorithms in computer vision and machine learning systems, to think through the meaning created by algorithmic structure and process. The aim is to use visual design to provoke new kinds of thinking and criticality that can offer opportunities to address algorithms in their increasingly more politicized role today. These new approaches are developed from an arts research perspective to support critical thinking and arts knowledge through creative coding and interactive design.

Computational Analysis of the U.S. Forest Fires

This paper analyses forest fires (FF) in the U.S. during 1984–2013, based on data collected by the monitoring trends in burn severity (MTBS) project. The study adopts the tools of dynamical systems to tackle information about space, time, and size. Computational visualization methods are used for reducing the information dimensionality and to unveil the relationships embedded in the data.