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Scheme mapping for relational database transformation to ontology: A survey

Mayadewi P.a, Sitohang B.b, Azizah F.N.b

a Universitas Telkom, Bandung, 40257, Indonesia
b Institut Teknologi Bandung, Bandung, 40132, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2017 IEEE.Ontology has an important role in creating semantic data on web semantics. Developing a new ontology model for a knowledge domain is not an easy process. Several existing studies, trying to obtain knowledge from existing assets, that is relational data model. The fundamental problem in the process of transforming relational database to ontology is how to construct an ontology model and extracting hidden semantics from relational model. Relational model are recognized as less expressive and incapable of supporting some conceptualizations. In this paper, we will provide an overview of the mapping scheme approach for transforming relational databases to ontologies based on literature studies from several studies that have been conducted. The results of the study concluded that the mapping scheme process for relational database transformation to ontology should consider all possible combinations of primary and foreign keys in relational model to produce a rich ontology.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Hidden semantics,Knowledge domains,Literature studies,Ontology model,Relational data models,Relational Database,Relational Model,transformation[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]ontology,relational database,scheme mapping,semantics,transformation[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICODSE.2017.8285866[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]