A genericmethodology for geo-related data semantic annotation

摘要

Geo-related data, also known as spatial data, is represented using a vector used for representingrnlongitude, elevation, and latitude. Specially built systems, well known as Geographical InformationrnSystems (GIS), made use of such data for querying, manipulating, navigation, and analyzing. Inrnthe current era of data, science needs to involve smart interactive investigation involving Internetrnof Data (IoD) on predicting upcoming changes and spatial updates on the map is growing rapidly.rnTo resolve issues concerning real-time spatial data, transformation using semantic annotation canrnprovide a better way to translate spatial relationships. These spatial relationships will supportrnspatial analysis by linking different cause and effect with the help of reasoning mechanism. Thisrnresearch's major focus is on a data transformation methodology for geo-related semantic annotation.rnSpatial dataset gets stored in a database and then transformed into Extensible MarkuprnLanguage (XML) and ResourceDescription Framework (RDF). Even for bi-directional transformationrnto work properly, we need to map different schema level transformations. A deep researchrnis conducted to consider available mappings, implementations, and updates to further improvingrndata fusion for having better compatibility. Then, transformed data as results get analyzedrnand discussed based on the data mapping rules formulated. It is aimed to show the importancernof reducing the response time of investigation and offer compatibility between the web andrnsemantically enriched spatial data.