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An Interactive Tool for Visualizing and Analyzing Spatio-Temporal Data
Abstract
Spatio-temporal data analysis has gained a degree of importance with the emergence of widespread location sensor technologies and applications generating data from activities such as location based GSM services and credit card transactions recorded by POS machines. By analyzing large-scale spatio-temporal data, companies can perform quality control for their services, and predict customer behavior. In this chapter, we introduce an interactive and configurable tool that effectively visualizes spatio-temporal data using two-dimensional cluster heat maps along with temporal histograms. We divide each dataset into geographical grids, cluster data within each grid, visualize clusters as heat maps, and finally calculate similarity scores between pairs of map images to help detect recurring patterns. We employ the tool in analyzing activity data of a GSM operator's friend-finder service and credit card transaction data of Akbank, a major bank in Turkey. We report examples of patterns observable using our tool, that are not otherwise observable.
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