Data management at Kenting's underwater ecological observatory

The management of real-time streaming data in large-scale collaborative applications presents major processing, communication and administrative challenges. To that end, an open-source RBNB DataTurbine provides an excellent basis for developing robust streaming data middleware. The current RBNB DataTurbine streaming data middleware system satisfies a core set of critical infrastructure requirements including reliable data transport, the promotion of sensors and sensor streams to first-class objects, a framework for the integration of heterogeneous instruments, and a comprehensive suite of services for data management, routing, synchronization, monitoring, and visualization. As a part of PRAGMA telescience group, in collaboration with the National Center for High-Performance Computing (NCHC) Taiwan, researchers at the San Diego Supercomputer Center (SDSC) deployed RBNB DataTurbine-based system to acquire data from underwater cameras (in the ocean) at Kenting. More specifically, we describe a system that integrates sensors (underwater video cameras) with computing and storage Grids to create a complete fabric for conducting e-Science. The system is currently used for observation by marine research scientists at the Research Center for Biodiversity. Academia Sinica in Taiwan. The described system increased performance and availability of the captured videos and we are, so far, pleased with its results.