An intelligent information fusion system for handling the archiving and querying of terabyte-sized spatial databases

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Abstract
NASA’s Intelligent Data Management Project is conducting research into the development of data management systems that can handle the archiving and querying of data produced by Earth and space missions. Several unique challenges drive the design of these systems, including the volume of the data, the use and interpretation of the data’s temporal, spatial, and spectral components, the size of the userbase, and the desire for fast response times. The Intelligent Data Management group has developed an Intelligent Information Fusion System (IIFS) for testing approaches to handling the archiving and querying of terabyte‐sized spatial databases. Major components of this system are the mass storage and its interactions with the rest of the system; the real‐time planning and scheduling for processing the data; the extraction of metadata and subsequent construction of fast indices for organizing the data along various search dimensions; and the overall user interface. The IIFS design is novel in a number of areas. Semantic data modeling techniques are used to organize the mass storage system to reduce the transfer times of the data to on‐line devices and the mechanical motions of the supporting robotics. Data percolates from near‐line mass storage to on‐line disk storage based upon its frequency of use. A combination of neural networks and expert systems defines how metadata is extracted to build up search indices to the underlying database. The metadata itself is organized in an object‐oriented database which has special data structures for representing the multiple views of the data (such as temporal, spatial, spectral, project, sensor) without resorting to redundant copies of information. A special data structure that maps directly between the Earth and a sphere organizes the data for efficient spatial querying. Enhancements to this data structure permit searches for images of differing extents and resolutions. The user interface is configured dynamically at run‐time depending on the scientist’s discipline and the current knowledge in the object database. This paper reports on the current implementation and planned extensions to an intelligent information fusion system for handling terabyte‐sized spatial databases.

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