A web-based, interactive visualization tool for social environmental survey data

Understanding human motivations and actions related to environmental problems is central to modeling complex, human-natural systems. However, social science survey data on environmental issues are often presented in relatively static reports and figures and are not easily accessible for participatory deliberation. Federal data sharing mandates motivate innovative data visualization and sharing mechanisms. We developed an open-source, web-based Survey Data Viewer as a visual interface to explore quantitative social science survey data. We used the Python Django web framework and the D3.js visualization library to create and deploy the tool. The Viewer was implemented using a water-related survey administered to a large, random sample of Utah adults in public venues. The Viewer allows users to visualize question responses based on demographic variables with percentages and mean response levels. We developed a standardized template for encoding survey data and metadata that permits the generalization of the tool to other similar surveys.