Knowledge-enriched Schema Mapping: A Preliminary Case Study of e-MedSolution System
Abstract
In this work, we investigated the framework of knowledge-enriched schema mapping and ontology learning, and highlighted the feasibility of utilizing these frameworks in heterogenous schema mapping and data integration. In particular, a preliminary case study was conducted to illustrate how the knowledge-enriched schema mapping and ontology leaning could be utilized to migration and integration of heterogenous database. More precisely, we introduced the structure and data tables of e-MedSolution and OMOP CDM, and analyzed the heterogeneity of these two data models initially. Furthermore, we designed a schematic diagram for schema mapping between clinical module of e-MedSolution and OMOP CDM clinical data and health system data. Moreover, we investigated how the existing knowledge bases and ontology learning could provides a semantic reference for vocabulary mapping and data table mapping between e-MedSolution and OMOP CDM. Finally, we summarized the main contribution of this work and gave the directions of future work.
