Research on semantic-based data integration
Xinyue Yang, Shenglin Li · 2023
With the development of information technology, "information silo" problem is getting serious, which hinders the exchange of information between enterprises. Data integration is the key technology to solve this problem, but traditional data integration methods have problems such as weak scalability and differences in language representation. In this paper, a method is proposed to complete data integration by establishing ontology, data mapping and semantic inference, which effectively solves the differences in data structure, data source and language representation and has strong scalability. In order to verify the feasibility of the method, experiments are conducted in this study with data describing people, and the completion of ontology construction, data mapping and semantic reasoning illustrates that the experiments achieve the expected results. Finally, the ontology model of nucleic acid detection is constructed in this paper, and the integration of nucleic acid detection data is completed to verify the feasibility of engineering the method.