Creating and visualizing data together in context: physicalizations for understanding environmental challenges with communities

Abstract

The environmental risks our society faces are becoming increasingly urgent and may have devastating implications both locally and globally. Members of the human-computer interaction and data visualization communities have sought to address environmental issues, primarily by developing technologies and visualization tools that share information or prompt individual behavior change, such as reducing home electricity usage. While these projects play an important role, we also need methods that consider the collective nature of many environmental issues.

This talk explores how interactive data physicalizations can help us understand and address environmental issues in our communities. I will discuss the design, fabrication, and use of SeeBoat, a remote control boat with LEDs and a customized low-cost sensing system that displays water quality data on-site and in real time in order to create hyper-local environmental data and make water quality issues visible, engaging, and interactive. I also describe the Data Lanterns project, a community-based data physicalization of local water quality permit violations from publicly available government data. I explore findings from these projects, including their scientific and social impacts on water quality systems.

Finally, I discuss how this work can inform human-data interaction and further the development of interdisciplinary research methods in computer science. These approaches are central as computer science takes on difficult large-scale problems in areas such as health care, wellness, and urban design.