A web-based, interactive visualization tool for social environmental survey data. (October 2016)

• Record Type: Journal Article
• Authors: Jones, Amber Spackman; Horsburgh, Jeffery S.; Jackson-Smith, Douglas; Ramírez, Maurier; Flint, Courtney G.; Caraballo, Juan
• Is Part Of: Environmental modelling & software. Volume 84(2016:Oct.)
• Page Start: 412
• Page End: 426
• Publication Date: 2016-10
• Subjects: Social science -- Survey data -- Visualization -- D3.js -- Python -- Django; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.07.013
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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. Highlights: We developed a Survey Data Viewer for web-based visualization of social survey data. The Viewer can be implemented for any quantitative survey data. The code is open-source for adoption and further development. The Viewer was used for a survey of water-related questions administered to 6000 adults. The tool is useful for understanding human dimensions of environmental issues.