Spatial and Temporal Target Association through Semantic Analysis and GPS Data Mining

We present an application for analyzing temporal and spatial interaction in an Association Network environment based on integrating Global Positioning Systems (GPS) Data, RDF Metadata and Data Mining. We argue that GPS data contains important information about relationships between people, through location and time, and can ultimately provide ideas about their association level and activities. We propose RDF Metadata and Data Mining can discover these Semantic Associations between entities, from which further insight into past, present and future associations and activities can be determined. We visualize our findings to illustrate effectiveness and also to persuade the user of the feasibility of our system called “GPODS” (Global Positioning Ontological Data System). Ultimately, we argue that GPODS adopts a reasonable methodology which Association Network Analysis can use at this juncture of the GPS data “explosion” to bring association context to GPS data.