How does a parent choose the best school for their child? Dust is an ongoing research project developed for Iridescent, an American NGO. The project’s aim is to provide a freely available, web based information visualization tool that supports parents in exploring and comparing the educational offerings (from Pre-K to High School) from selected major cities in the United States, currently: New York, Los Angeles, and the San Francisco Bay Area. By leveraging a step-by-step decision making process, Dust helps to evaluate and compare school profiles based on multidimensional data-sets composed of general information (e.g., enrollment, class size, number of teachers), school performances (e.g., subjects score and proficiency, attendance), and urban mobility (e.g., location, distances, transportation). Supported by geographical maps and close-up visualizations users can create custom profiles based on their needs and priorities and then perform a search for the most appropriate schools for their children. Dust aims to combine the capability of information visualization in depicting synthetic views of complex, multidimensional, and georeferenced data; with a rich, yet intuitive, web-user experience. The project aims to move away from a “by experts, for experts” design paradigm to a schools comparison information visualization “for the people” -providing real impact on their daily life, and future prospects, through improved choices.

Dust: A Visualization Tool Supporting Parents’ School-Choice Evaluation Process

AZZI, MATTEO;CAVIGLIA, GIORGIO;RICCI, DONATO;CIUCCARELLI, PAOLO;
2011

Abstract

How does a parent choose the best school for their child? Dust is an ongoing research project developed for Iridescent, an American NGO. The project’s aim is to provide a freely available, web based information visualization tool that supports parents in exploring and comparing the educational offerings (from Pre-K to High School) from selected major cities in the United States, currently: New York, Los Angeles, and the San Francisco Bay Area. By leveraging a step-by-step decision making process, Dust helps to evaluate and compare school profiles based on multidimensional data-sets composed of general information (e.g., enrollment, class size, number of teachers), school performances (e.g., subjects score and proficiency, attendance), and urban mobility (e.g., location, distances, transportation). Supported by geographical maps and close-up visualizations users can create custom profiles based on their needs and priorities and then perform a search for the most appropriate schools for their children. Dust aims to combine the capability of information visualization in depicting synthetic views of complex, multidimensional, and georeferenced data; with a rich, yet intuitive, web-user experience. The project aims to move away from a “by experts, for experts” design paradigm to a schools comparison information visualization “for the people” -providing real impact on their daily life, and future prospects, through improved choices.
Data visualization; Geographical information systems; Cartography; Open Data; Decision support
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/684701
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