The Requirements for Ontologies in Medical Data Integration: A Case Study

TL;DR

This paper discusses the requirements for ontologies in medical data integration, illustrating the approach through a case study on Juvenile Idiopathic Arthritis within the Health-e-Child project, emphasizing data sharing and knowledge management.

Contribution

It presents a requirements specification approach for biomedical data integration, focusing on ontologies in a complex, multi-level medical data environment.

Findings

Requirements elicitation for JIA case study

Ontology-based data integration framework

Insights into biomedical data sharing challenges

Abstract

Evidence-based medicine is critically dependent on three sources of information: a medical knowledge base, the patients medical record and knowledge of available resources, including where appropriate, clinical protocols. Patient data is often scattered in a variety of databases and may, in a distributed model, be held across several disparate repositories. Consequently addressing the needs of an evidence-based medicine community presents issues of biomedical data integration, clinical interpretation and knowledge management. This paper outlines how the Health-e-Child project has approached the challenge of requirements specification for (bio-) medical data integration, from the level of cellular data, through disease to that of patient and population. The approach is illuminated through the requirements elicitation and analysis of Juvenile Idiopathic Arthritis (JIA), one of three diseases being studied in the EC-funded Health-e-Child project.