Focus Set Subontologies and Semantic Differences for Large ELH Ontologies

Abstract

Ontologies have been widely used in a variety of fields to serve as sources for formally structured knowledge. The Systemized Nomenclature of Medicine - Clinical Terms (SNOMED CT) ontology, among others, is widely used in the (bio-)medical domain, as it provides a comprehensive multilingual vocabulary for capturing all aspects of electronic health records and clinical knowledge, resulting in a very large and complex ontology. Ontology extraction methods enable efficient use of such large ontologies by splitting them into interconnected smaller parts. This thesis presents a novel method for extracting focus set subontologies from ELH ontologies for a set of symbols selected by the user. The resulting subontologies satisfy the requirements sought by SNOMED CT users, including providing complete semantics for the description of input symbols while being concise and conforming to SNOMED CT modelling principles. The findings show that, in comparison to locality-based modularisation and uniform interpolation, the resulting subontologies satisfy the requirements of SNOMED CT in terms of size, encapsulating the entire semantics of the definitions solely for the set of input symbols, and retaining the original ontology's structure. This thesis also investigates the computation of semantic differences between extracted subontologies using a combination of our notion of subontologies and the uniform interpolation-based semantic difference method in order to constrain the development of such differences to a particular subdomain of the ontology identified by the user. The findings demonstrate that our method is capable of revealing differences in the meaning of focus concept definitions associated with a particular subdomain of the ontology, where some of these differences would not have been generated without this focused approach to tracking semantic differences between ontologies.

Date of Award	31 Dec 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Renate Schmidt (Supervisor) & Andrea Schalk (Supervisor)