(Faculty of Computing and Information Technology, King Abdul aziz University, Saudi Arabia)(2) Omar Mohammed Barukab
(Faculty of Computing and Information Technology, King Abdul Aziz University, Saudi Arabia)(3) Norazah Yusof
(Faculty of Computing and Information Technology, King Abdul Aziz University, Saudi Arabia)(4) Nataniel Dengen
(Faculty of Computer Science and Information Technology, Mulawarman University, Indonesia)(5) Haviluddin Haviluddin
(Faculty of Computer Science and Information Technology, Mulawarman University, Indonesia)(6) Mohd Shahizan Othman
(Faculty of Computing, University Teknologi Malaysia, Malaysia)*corresponding author
AbstractThe diversity of applications developed with different programming languages, application/data architectures, database systems and representation of data/information leads to heterogeneity issues. One of the problem challenges in the problem of heterogeneity is about heterogeneity data in term of semantic aspect. The semantic aspect is about data that has the same name with different meaning or data that has a different name with the same meaning. The semantic data mapping process is the best solution in the current days to solve semantic data problem. There are many semantic data mapping technologies that have been used in recent years. This research aims to compare and analyze existing semantic data mapping technology using five criteria’s. After comparative and analytical process, this research provides recommendations of appropriate semantic data mapping technology based on several criteria’s. Furthermore, at the end of this research we apply the recommended semantic data mapping technology to be implemented with the real data in the specific application. The result of this research is the semantic data mapping file that contains all data structures in the application data source. This semantic data mapping file can be used to map, share and integrate with other semantic data mapping from other applications and can also be used to integrate with the ontology language.
KeywordsOntology; Education Domain; Semantic approach
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DOIhttps://doi.org/10.26555/ijain.v3i3.131 |
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