Hetero-GCD2RDF: An Interoperable Solution for Geospatial Climatic Data by Deploying Semantic Web Technologies

Abstract

Ocean and Land based satellite observation system comprises of various sensors and configurations. The generated Geospatial Climatic Data (GCD) by sensors is transmitted in heterogeneous file formats with heterogeneous vocabularies that lead to semantic heterogeneity of data. Government and public organizations started to publish these datasets to users through climatic web portals. The critical task in handling heterogeneous files is data interpretation and interoperability. This can be handled by facilitating the data to reach semantically structured or linked data. This paper proposes a Hetero-GCD2RDF data retrieval approach that focuses on two aspects (1) Extraction of records from satellite data and represent it as linked data namely Resource Description Framework (RDF) and (2) Implementation of SPARQL query engine to the resultant RDF for data retrieval. Data from Indian Meteorological Satellite INSAT-3D is taken as a typical example to execute the proposed approach. Where, approximately 170 files of about 650 MB in memory containing 1,278,000 records have been converted and queried. Compared to conventional methods the proposed method saves nearly 38.12% of time to represent the data in RDF. Thus, the proposed Hetero-GCD2RDF approach is recognized to be efficient, reliable and suitable for semantic web.