The NEXRAD radar network comprises 120 operational WSR-88D Doppler radars in the continental United States that are run by the National Weather Service. The Doppler radar data is unique among ground-based atmospheric observations because it provides the highest spatial and temporal resolution information available within three-dimensional volumes on a continuous basis, regardless of the weather present.
Each year across the United States, floods, hail, strong winds, lightning, and winter storms - so-called meso-scale weather events - result in annual economic losses greater than $13B. LEAD addresses this problem through an integrated, scalable framework for use in accessing, preparing, assimilating, predicting, managing, mining/analyzing, and displaying a broad array of meteorological and related information, independent of format and physical location.MyLEAD is a personal metadata catalog, a key tool in a management of data products used in or generated by computational investigations on the grid. The catalog is a web service in that the primary mode of interaction with the service is through XML and SOAP. The benefits of myLEAD are its support for 1.) publishing and sharing of data products, collections of products, and full experiments; 2.) semi user-transparent structuring of the data, and 3.) versioning of experiments through time.
Calder is a continuous query grid service that brings data streams to grid as a single coherent data resource. Calder extends OGSA-DAI and dQUOB.
dQUOB is a middleware system providing continuous evaluation of queries over time sequenced data. The system provides access to data in data streams by means of SQL queries. The queries are dynamically embedded into the data streams at runtime, and managed remotely during application execution. dQUOB SQL queries have the power to filter and aggregate data, combine streams, and create new streams. Support for embedded user defined functions provides data transformation capabilities. dQUOB is targeted towards data streaming parallel and distributed computations such as scientific visualization, performance monitoring, and large-scale sensor data. The dQUOB system has been applied to such diverse applications as a safety critical autonomous robotics simulation, and scientific software visualization for global atmospheric transport modeling.
The Relational Grid Resource project explores the representation of grid resource data. Grid information includes information and attributes about resources in a computational or data grid, including compute servers, clusters, storage resources, people, groups of people, etc. We posit that the needs of the computations that run on a grid impose a unique set of demands on a resource repository that are not being met by the current hierarchical or attribute-value approaches to directory services. Specifically, user-driven needs necessitate support for complex queries over the resource repository and the timeliness needs require policies about update rates to the data contained in the repository. Our approach explores relational database-based technology for management of grid resource information.
This work is being done in conjunction with the Unified Relational Grid Information Services project under Peter Dinda at Northwestern.