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Integrating terminologies into standard SQL: a new approach for research on routine data.

André Sander1, Roland Wauer2

  • 1ID GmbH & Co. KGaA, Platz vor dem Neuen Tor 2, 10115, Berlin, Germany. asander@id-berlin.de.

Journal of Biomedical Semantics
|April 25, 2019
PubMed
Summary

This study introduces an innovative approach to semantically analyze electronic medical records by enabling direct semantic queries on SQL databases. The developed Ontology-SQL (O-SQL) system achieves high accuracy in processing unstructured medical data.

Keywords:
Data mining (knowledge discovery)Infant mortalityOntology-based queriesTerminology serverTranslational research

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Area of Science:

  • Biomedical Informatics
  • Database Management
  • Natural Language Processing

Background:

  • Electronic medical records (EMRs) contain substantial free-text data requiring semantic evaluation.
  • Current methods necessitate data encoding or transformation into knowledge-based databases for analysis.

Purpose of the Study:

  • To develop a method for direct semantic querying of SQL databases without data transformation.
  • To enable efficient analysis of free-text data within EMRs.

Main Methods:

  • Developed Ontology-SQL (O-SQL), an extension to SQL for semantic expressions.
  • Implemented a framework using a terminology server for annotating free-text database tables.
  • Created a parser to translate O-SQL queries into SQL for database execution.

Main Results:

  • Successfully reproduced existing semantic queries in a condensed format.
  • Achieved high annotation quality with 97.62% sensitivity and 100.00% specificity.
  • Semantic queries demonstrated high performance with F-scores ranging from 0.91 to 0.98.

Conclusions:

  • Systematic analysis of free-text EMR data is feasible using standard tools.
  • Integrating ontologies with database technologies is crucial for unstructured data analysis.
  • The technology supports relational data and advances translational research.