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Towards a Semantic Data Harmonization Federated Infrastructure.

Catalina Martinez-Costa1,2, Francisco Abad-Navarro1,2

  • 1University of Murcia, Murcia, Spain.

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Summary
This summary is machine-generated.

This study introduces a data harmonization infrastructure for virtual data integration in medical informatics. It enables homogeneous querying of heterogeneous data across institutions without data leaving its source.

Keywords:
OntologiesSNOMED CTgraph databasesemantic harmonization

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Area of Science:

  • Medical Informatics
  • Data Science
  • Ontology Engineering

Background:

  • Increasing need for data integration in medical informatics projects.
  • Challenges with semantically and syntactically heterogeneous data across institutions.
  • Restrictions on data sharing often mandate virtual data integration, preventing data movement.

Purpose of the Study:

  • To propose a data harmonization infrastructure for virtual data integration.
  • To enable homogeneous querying of distributed, heterogeneous biomedical data.
  • To address limitations imposed by data sharing agreements.

Main Methods:

  • Developed a data harmonization infrastructure utilizing a semantically rich common data representation.
  • Integrated content from biomedical ontologies like SNOMED CT using the BTL2 upper-level ontology.
  • Imported the common data model into a graph database for querying.

Main Results:

  • Successfully integrated three distinct datasets using the proposed infrastructure.
  • Demonstrated the feasibility of the approach through test queries.
  • Enabled homogeneous querying across previously disparate data sources.

Conclusions:

  • The proposed data harmonization infrastructure facilitates virtual data integration for heterogeneous biomedical data.
  • The approach supports efficient and homogeneous querying without centralizing sensitive information.
  • This method is a feasible solution for complex medical informatics challenges requiring data sharing.