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Ontology mapping for semantically enabled applications

Harrow, I., Balakrishnan, R., Jimenez-Ruiz, E. ORCID: 0000-0002-9083-4599, Jupp, S., Lomax, J., Reed, J., Romacker, M., Senger, C., Splendiani, A., Wilson, J. and Woollard, P. (2019). Ontology mapping for semantically enabled applications. Drug Discovery Today, doi: 10.1016/j.drudis.2019.05.020

Abstract

In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential of semantically enabled or enriched applications and for meaningful insights, such as drug discovery, using machine-learning technologies. We discuss challenges and solutions for better ontology mappings, as well as how to select ontologies before their application. In addition, we describe tools and algorithms for ontology mapping, including evaluation of tool capability and quality of mappings. Finally, we outline the requirements for an ontology mapping service (OMS) and the progress being made towards implementation of such sustainable services.

Publication Type: Article
Additional Information: © 2019 The Authors. Published by Elsevier Ltd.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RM Therapeutics. Pharmacology
Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Date Deposited: 03 Oct 2019 10:41
URI: https://openaccess.city.ac.uk/id/eprint/22924
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