Hosted by BostonCHI
What is visual evidence? How do we know we can trust a data set? The methods of data visualization can help us discover patterns and inconsistencies in data sets, but are bound to the limits of symbolic representation – they can only begin when data already exists. Consequently, data is silent about its origins remains disconnected from the phenomena it supposedly represents. In my talk, I will discuss autographic visualization as a countermodel to data visualization. Autographic visualization describes a set of design principles and visual practices to reveal traces and material evidence. Autographic visualization aims to make data collection accountable and engaging, which can play an important role in discourses around climate change, pollution, and evidence construction.