Querying Spatial and Temporal Data by Condition Tree: Two Examples Based on Environmental Issues

Abstract

The need to perform complex analysis and decision making tasks has motivated growing interest in Geographic Information Systems (GIS) as a means to compare different scenarios and simulate the evolution of phenomena. However, data and function complexity may critically affect human interaction and system performances during planning and prevention activities. This is especially true when the scenarios of interest involve space or time in imprecise contexts. In this paper we propose a visual language which drives users to perform queries involving discrete objects by considering their temporal component. Moreover, in order to allow queries closer to the user mental model we add a specific hint for relaxing constraints and allowing fuzzy conditions. The visual language will be tested on two specific contexts concerning with the fire risk and the air pollution

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