2004 · 27 citations · 7 references
ComputingComputer ScienceEarth SciencesData ManagementGeographic Information SystemsGrid ComputingData IntegrationGeospatial MetadataGeospatial OntologiesMetadata ManagementSpatial Data CataloguesSpatial Data Infrastructure ArchitectureGeospatial Metadata StandardsHeterogeneous Data ManagementMetadataOpen Science InfrastructureService RegistrySpatial Data CatalogingSpatial Data Infrastructure OntologiesVirtual Organization Architecture
Grid infrastructure enables sharing of heterogeneous resources via Virtual Organizations, but its current registry mechanisms, such as MCS, are insufficient for domain‑specific resource discovery. This paper proposes extending Grid MCS with an OGC Web Registry Service wrapper to enable geospatial querying across heterogeneous spatial data sources in earth‑science grids. The approach incorporates ontology‑based semantic inference to integrate diverse spatial data models and is demonstrated within the NASA Grid Data Service environment.
Grid is a promising e-Science infrastructure that promotes and facilitates the sharing and collaboration in the use of distributed heterogeneous resources through Virtual Organization (VO). A critical factor to the overall utility of Grid is a scalable, flexible and robust registry mechanism. Although it provides some mechanisms to store and access metadata for publishing and discovering resources, such as MCS (Metadata Catalog Service), the Grid registry is inadequate for dealing with domain-specific resources. To enhance the earth science Grid systems, this paper presents a geospatial registry approach in which the OGC (Open GIS Consortium) WRS (Web Registry Service), a <i>de facto</i> standard that supports the publishing of and run-time access to geospatial resources, as a wrapper is used to extend the capabilities of the conventional Grid MCS to the processing of geospatial queries against multiple heterogeneous spatial data sources and services. The approach presented not only focuses on the specifics of descriptive information about spatial data, services, and relevant information objects, but also emphasizes using ontology to infer the semantic relationships between vocabularies for integrating different information models. The implementation of presented approach used in NASA Grid Data Service environment is also illustrated in this paper.
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