Semantics-Preserving RDB2RDF Data Transformation Using Hierarchical Direct Mapping
Source abstract
Abstract
Direct mapping is an automatic transformation method used to generate resource description framework (RDF) data from relational data. In the field of direct mapping, semantics preservation is critical to ensure that the mapping method outputs RDF data without information loss or incorrect semantic data generation. However, existing direct-mapping methods have problems that prevent semantics preservation in specific cases. For this reason, a mapping method is developed to perform a semantics-preserving transformation of relational databases (RDB) into RDF data without semantic information loss and to reduce the volume of incorrect RDF data. This research reviews cases that do not generate semantics-preserving results, and the corresponding problems into categories are arranged. This paper defines lemmas that represent the features of RDF data transformation to resolve those problems. Based on the lemmas, this work develops a hierarchical direct-mapping method to strictly abide by the definition of semantics preservation and to prevent semantic information loss, reducing the volume of incorrect RDF data generated. Experiments demonstrate the capability of the proposed method to perform semantics-preserving RDB2RDF data transformation, generating semantically accurate results. This work impacts future studies, which should involve the development of synchronization methods to achieve RDF data consistency when original RDB data are modified.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Semantic Web and Ontologies · Service-Oriented Architecture and Web Services · Advanced Database Systems and Queries
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Openub, Seoul 06097, Korea
School of Information Convergence, Kwangwoon University, Seoul 01890, Korea
Funding
Ministry of Science and ICT, South Korea
References (38)
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