Instances transformation method based on semantic web for completing data sources
Ekasari Nugraheni · 2017
Availability at large-scale semantic web data can be considered as an opportunity to be used in data source analysis. This analysis process might not obtain data as required since the data is extracted from external sources. This incompleteness of data source can affect analysis result. To resolve this problem, this paper proposed a method for generating data from a transformation process that built based on semantic web technology (ontologies). The application will apply an algorithm that can find a superclass and a subclass of superclass ontology, by mapping the instances of relevant object property to the ontology classes. The classes are then added to the source as a data object instances. In the mapping process, the data is represented by using semi structured format RDF (Resource Description Framework). Data instances generated from this mapping process will complete the semantic data sources and then support the analysis process.