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Updated: Jun 15, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Using ontologies for structuring organizational knowledge in Home Care assistance.

Aida Valls¹, Karina Gibert, David Sánchez

¹Department of Computer Science and Mathematics, Universitat Rovira i Virgili, Av Països Catalans 26, 43007 Tarragona, Catalonia, Spain. aida.valls@urv.cat

International Journal of Medical Informatics

|February 27, 2010

Summary

This study demonstrates how ontologies can formalize healthcare knowledge for better management of distributed systems. This approach enhances flexibility, adaptability, and efficiency in e-health applications, particularly in senior home care.

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Last Updated: Jun 15, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Area of Science:

Health Informatics
Knowledge Engineering
Ontology Engineering

Background:

Complex distributed health systems require improved management through information technologies.
Supporting multidisciplinarity and seamless communication is essential for healthcare professionals.
Senior Home Care is a strategic area in ageing Europe, necessitating efficient distributed systems.

Purpose of the Study:

To propose the ontological paradigm for describing organizational knowledge in complex healthcare institutions.
To detail the ontology engineering process and methods for maintaining it.
To analyze the exploitation of ontologies in real healthcare applications, focusing on senior home care.

Main Methods:

Ontology design based on a European consortium's Home Care medical model.
Application of the On-To-Knowledge ontology engineering methodology.
Formalization of medical entities into ontological classes with hierarchies and properties.

Main Results:

Feasibility confirmed: ontological paradigm and modern languages can describe medical knowledge.
A complete, non-ambiguous definition of the Home Care model was achieved.
Exploitation in a knowledge-driven e-health application showed benefits in flexibility, adaptability, and efficiency.

Conclusions:

Ontologies can non-ambiguously represent terminology and formalize interrelations in distributed healthcare.
Ontologies facilitate adaptation to organizational changes and support profile-based interaction models.
Formalizing organizational interrelations via ontologies is key for effective knowledge-driven e-health systems.