Metadata model, resource discovery, and querying on large scale multidimensional datasets. The GEREQ project

At present, geographic image databases make very limited use of metadata. There is a need to somehow manage a meta-level system on top of such a kind of information systems. Issues in this field include a representation model for geographic data, the relationship between metadata and resource discovery on geographic data, and efficient query processing in a distributed environment. In such a background, the GEREQ project is targeted to address three critical aspects: (1) clustering approaches that can detect clusters of arbitrary shape of multidimensional data, which are generated from geographic images; (2) metadata model that formulates the metadata for the integrated system to direct a query to relevant databases; (3) development of theoretical foundation of database selection approaches based on the metadata; and (4) query processing approaches that integrate heterogeneous queries extracted from the content of image data. Furthermore, fundamental understanding of relationships between metadata and resource discovery on multidimensional data will be tackled. Results obtained from this research are critical to retrieval on large volumes of multidimensional data distributed over the Internet and will find broad applications as a template for the development of systems which manage multidimensional data. Experimental results will enable the establishment of effective benchmarks for assessing the performance of distributed geography image data retrieval systems.