Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas

Area of Science:

• Biomedical Informatics
• Data Science
• Medical Research

Background:

• Data sharing is crucial for reproducibility and reuse in medical sciences.
• FAIR data principles (Findable, Accessible, Interoperable, Reusable) are essential for effective data sharing.
• The Leipzig Health Atlas (LHA) platform aims to facilitate FAIR data principles in health research.

Purpose of the Study:

• To describe the integration of three key components: SEEK, LHA Data Portal, and PhenoMan.
• To demonstrate how PhenoMan's ontological phenotype modeling can generate executable queries for the LHA Data Portal.
• To showcase the application of this integrated approach within the Leipzig Health Atlas.

Main Methods:

• Leveraging the SEEK management platform for data archiving and sharing.
• Utilizing the LHA Data Portal for managing study metadata and data retrieval.
• Employing PhenoMan, an ontological framework, for phenotype modeling and query generation.
• Developing a domain-specific query language (SDQL) compatible with CDISC ODM standards for data management systems.

Main Results:

• Successful integration of PhenoMan for phenotype modeling within the LHA platform.
• Demonstrated ability to generate phenotype-based search queries using PhenoMan.
• Queries generated in SDQL are executable by the LHA Data Portal, facilitating data discovery.
• The combined system supports the representation and querying of phenotypes in the Leipzig Health Atlas.

Conclusions:

• The integrated LHA platform, combining SEEK, LHA Data Portal, and PhenoMan, effectively supports FAIR data principles.
• Ontological phenotype modeling provides a powerful mechanism for data retrieval and reuse in health research.
• This approach enhances the value of health data by enabling complex querying and promoting scientific reproducibility.