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An Extendible Realism-Based Ontology for Kinship.

Michael Rabenberg1, Anuwat Pengput1, Werner Ceusters1

  • 1University at Buffalo, 77 Goodell Street, Buffalo NY, 14203, USA.

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|May 29, 2024
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Summary

This study introduces a novel kinship ontology aligned with the Basic Formal Ontology (BFO). It enhances medical and biomedical data by providing robust representation of family relationships and aiding in error detection.

Keywords:
BFO2020Kinship ontologySNOMED CT

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Area of Science:

  • Biomedical Informatics
  • Ontology Engineering
  • Medical Data Representation

Background:

  • Accurate representation of kinship is vital for medical and biomedical applications.
  • Existing kinship ontologies do not align with the Basic Formal Ontology (BFO) standards.

Purpose of the Study:

  • To propose a novel kinship ontology that adheres to BFO principles.
  • To improve the representation of kinship relations in biomedical contexts.

Main Methods:

  • Developed a novel kinship ontology fully axiomatized in First Order Logic (FOL) following BFO2020-FOL rules.
  • Modularized the ontology into 6 Common Logic Interface Format (CLIF) files for flexible import.
  • Created bridging axioms for integration with SNOMED CT.
  • Incorporated a module with specialized axioms for detecting unusual kinship relations and potential data entry errors.

Main Results:

  • A novel, BFO-compliant kinship ontology has been developed.
  • The ontology is modular, axiomatized in FOL, and interoperable with SNOMED CT.
  • Includes a unique module for identifying and alerting on atypical kinship relationships.

Conclusions:

  • The proposed kinship ontology offers a standardized and robust framework for representing family relationships in biomedical informatics.
  • This ontology facilitates improved data accuracy and supports the identification of complex or erroneous kinship data.