Title: A Moving Objects Database Infrastructure for Hurricane Research: Data Integration and Complex Object Management
Author: Markus Schneider
Organization: University of Florida
Co-Authors: Shen-Shyang Ho, Malvika Agrawal, Tao Chen, Hechen Liu, Ganesh Viswanathan

Current web-based weather event and satellite data portals provide large amounts of data over a historical timeline. However, users of these portals often get access to only limited, pre-defined queries based on a strict set of criteria and event trajectories. Desirable capabilities, such as spatial-temporal analysis, efficient satellite data retrieval, and ad-hoc queries on trajectory data, are not available in these information systems and data archives. In this paper, we describe our current work and progress in the development of a sophisticated moving objects database infrastructure designed primarily to allow ad-hoc querying of dynamic atmospheric events (e.g., hurricanes and storm systems) and the efficient retrieval of satellite (e.g, QuikSCAT, TRMM) measurements. In particular, we describe our progress in the integration of tropical cyclone events data and satellite measurements from different sources into a single moving objects database system for scientific users to perform ad-hoc queries and sophisticated spatio-temporal analysis. Moreover, we describe how a user can remotely connect her personal analysis software to the database system to perform flexible query on tropical cyclone best track data and retrieve the associated satellite measurements. Finally, we show how complex objects like hurricane trajectories and massive satellite sensor trajectories with measurements can be effectively stored and handled in a database context using our novel iBLOB (Intelligent Binary Large Objects) data structure.