Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures.

Area of Science:

• Health Informatics
• Database Management
• Data Semantics

Background:

• Maintaining data integrity is vital for retrospective clinical studies and longitudinal analysis.
• Temporal models and knowledge models are essential for organizing data and enhancing query capabilities across institutions.
• Outdated data can lead to erroneous conclusions in clinical research.

Purpose of the Study:

• To present a modelling framework for temporal relational databases using an ontology.
• To derive a shareable and interoperable data model for clinical data.
• To demonstrate the impact of tracking organizational changes on data quality and healthcare activities.

Main Methods:

• Developed an ontology-driven database modelling approach (OntoRela).
• Utilized a temporal database modelling approach (Unified Historicization Framework).
• Applied the framework to hospital organizational structures to track changes.

Main Results:

• The framework successfully tracked organizational changes, impacting data quality assessment and healthcare activities.
• Demonstrated the utility of ontologies for formal, interoperable, and reusable data definitions.
• Showcased the adequacy of temporal databases for storing, tracing, and querying historical data.

Conclusions:

• An ontology-driven temporal relational database framework enhances data semantics and change tracking.
• This approach improves data quality, supports reproducibility in clinical analysis, and enables effective historical data querying.
• The framework provides a formal, interoperable, and reusable solution for managing complex healthcare data over time.