Abstract
AbstractSeveral satellite data receiving and distributing centers across the world support data storage, processing, and retrieval based on satellite, sensor, product, latitude, longitude, date and time, etc. These systems address queries on satellite products that are mostly high-level concepts. A more sophisticated retrieval system that supports ontological concepts, subconcepts, and concept hierarchical queries delivers refined results that broaden the scientific horizon of the application domain. To achieve this, the current research designed and implemented an ontology concept-based satellite data management and retrieval methodology. This enhances the performance of the satellite data retrieval system and supports semantic queries. The performance of the retrieval system depends upon the strategy followed to maintain domain ontologies and satellite data instances. Three ontology-based satellite data management strategies are discussed, and their performance was evaluated by taking real and benchmark metrics. A semantic query set of 25 queries was chosen covering various concepts, subconcepts, and concept hierarchical-related queries that involve various SPARQL query constructs. The test bed is taken from real-time satellite data received from Kalpana-1 of various sizes of triple stores.
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