A proposed methodology for Semantic Web implementation

Semantic Web provides precise, timely, searchable and well-define information across different sources of data. However, there is need of solving the problem of interoperability due to everyday increase of data from different sources. Whereby, the resourceful information or data integration between human and machines are needed. Thus, more precisely, this paper addresses an ultimate problem of integrating and utilizing the accurate data on information systems. The proposed methodology of this paper includes: (1) grounded theory that focuses on particular interaction between human and machines, (2) developing the analysis; the research introduces the Software Development Life Cycle (SDLC) approach, from the development to implementation stages, (3) sources of data; for state-of-the-art research, we propose to use MetOcean (Meteorological and Oceanographic) data, and (4) Research instrument which is to set our research into practice where we will build Semantic Web application using Franz AllegroGraph and use SIMILE (Semantic Interoperability of Metadata and Information in Unlike Environments). Finally, we provide the Ontology model of the for the state-of-the-art research in meteorological and Oceanographic domain.