Accumulation as a tool for efficient visualization of geographical and temporal data

In this paper, we describe a set of visualization methods with an accumulation tool to perform interactive data exploration. Accumulation maps or Kernel Density Estimation (KDE) maps, count the amount of data accumulated at a certain location. The accumulation tool addresses the cluttering issues when displaying large amounts of data. But the accumulation tool can also be used to unveil patterns, to detect outliers and flaws in datasets. Through these applied examples, we show how the accumulation tool and its real time applications take advantage of human vision and are therefore assets for data exploration and validation. As the accumulation tool uses GPU techniques, it can be used in real-time with large datasets.