Moving phenomenon: Aggregation and analysis of geotime-tagged contents on the Web

The analysis of movement of people, vehicles, and other objects is important for carrying out research in social and scientific domains. The study of movement behavior of spatiotemporal entities helps enhance the quality of service in decision-making in real applications. However, the spread of certain entities such as diseases or rumor is difficult to observe compared to the movement of people, vehicles, or animals. We can only infer their locations in a certain region of space-time on the basis of observable events. In this paper, we propose a new model, called as moving phenomenon, to represent time-varying phenomena over geotime-tagged contents on the Web. The most important feature of this model is the integration of thematic dimension into an event-based spatiotemporal data model. By using the proposed model, a user can aggregate relevant contents relating to an interesting phenomenon and perceive its movement behavior; further, the model also enables a user to navigate the spatial, temporal, and thematic information of the contents along all the three-dimensions. Finally, we present an example of typhoons to illustrate moving phenomena and draw a comparison between the movement of the moving phenomenon created using information from news articles on the Web and that of the actual typhoon.