Semantic Heterogeneity Management between Weather Systems Using Ontology Mapping
Kaladevi Ramar, A. R. Revathi, Shanmugasundaram Hariharan, A Bhanuprasad · 2022
Emergence of Information and Communication Technology (ICT) provides enormous volume of data over the WWW. Weather data one among them which is provided by different organizations with various formats and attributes. Weather data plays major role in various domains such as agriculture, forestry, disaster management. In order to effectively use the heterogeneous weather data, different processing techniques are used. This is useful for achieving interoperability and integration among similar systems. Our proposed system focuses on identifying the semantic and data heterogeneity between weather systems and resolve semantic incompatibilities by ontology mapping. The proposed technique is relied on background ontology which developed with all entities and attributes. The proposed algorithm OMFIM (Ontology Mapping For Information Management) performance is compared against state of the art algorithms S-match, COMA++ and Falcon-AO algorithms. Results show that the ontology matching of OMFIM is more optimum than the existing techniques and also applicable for the ontology with less terminological and schematic similarities.