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Metadata-Driven Approach to Generalisation of Transformations in ETL Processes.

Sara Bachir1, Abishaa Vengadeswaran1, Holger Storf1

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Summary
This summary is machine-generated.

A metadata-driven approach generalizes Extract, Transform, Load (ETL) processes for clinical data secondary use. This enhances data integration by reusing implementations through a metadata repository (MDR).

Keywords:
Data IntegrationETL processMDRMetadata-driven approachOMOP CDMmetadatarule-based approachsecondary use

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Area of Science:

  • Health Informatics
  • Data Management
  • Clinical Data Research

Background:

  • Secondary use of clinical data is increasingly vital.
  • Numerous Extract, Transform, Load (ETL) processes exist for specific data integration needs.
  • A metadata-driven approach offers generalized ETL processes for implementation reuse.

Purpose of the Study:

  • To generalize ETL processes for clinical data secondary use.
  • To enable reuse of existing ETL implementations through metadata.
  • To improve efficiency and flexibility in clinical data integration.

Main Methods:

  • Utilized a metadata repository (MDR) storing data attributes.
  • Incorporated ISO 21526 standards for metadata.
  • Applied W3C PROV model for governance and data provenance tracking throughout the data lifecycle.

Main Results:

  • Represented source and target system data structures within the MDR.
  • Defined element relationships and transformation rules.
  • Developed a generic ETL implementation driven by MDR content, externalizing use-case specifics.

Conclusions:

  • A rule-based, metadata-driven ETL implementation generalizes extract and load phases.
  • Further standardization of the transformation process is required.
  • A user-friendly interface is crucial for non-technical users to integrate expertise.