Abstract
The analysis of air quality data may reveal the quality of life and can prevent dangers for the citizen health. This paper presents an approach for air quality data analysis, which exploits Data Mining and InfoVis techniques to support the analysts daily work. The proposed approach addresses data generated by the electronic nose, a device that detects chemical compounds perceived by humans through the smell. A working pipeline implements a workflow for data processing with clustering techniques; an enhanced powerful calendar visualization combined with more traditional line graph and geo-referenced visualizations shows data to the analyst allowing to detect temporal trends and making immediate comparisons.
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