Ontology-Driven Approaches for Standardizing Rare Disease Terminology

Abstract

Rare diseases represent approximately 7000 disease entities that affect almost 3.5 % of the world
population. Each rare disease receives inconsistent nomenclature from different medical systems which
impedes research, diagnosis and treatment. In this paper, we study the problem of integrating rare disease
terminologies using semantic models through an ontology driven approach. Using existing ontological
datasets and ontology reasoners, we develop an upper ontology which automates the mapping and
alignment of diseases’ names and definitions within databases. The data interoperability, improved
retrieve and enhanced framework adaptability presented in the results demonstrate the effectiveness of the
system. This study presents an integration approach that gives precise and scalable solution for
harmonization of rare disease informatics terminologies.