Dynamic Data Representations for Spatio-temporal Data Visualization

Spatio-temporal computing can be viewed as a specific computation to link spatial features in physical or virtual spaces with simultaneously in discrete or continuous and asynchronous time steps. With the increase of temporal and spatial digital data sets, the importance of temporal, spatial, and spatio-temporal aggregation computation has been reflected in a significant number of disciplines. We develop a graph grammar based visual system with spatio-temporal relational grammars. The theoretical foundations are developed for reasoning tasks by the artificial intelligence and dynamic spatial interaction. We apply the spatio-temporal computing theory to process dynamic data visualization with interactions. The dynamic visual analytics designed to transform the data into some combination terms that we can understand more easily. The presentation algorithms may produce an interactive streaming media on the screen. We can also use motion as a display technique to represent data that is either static or dynamic.