Skip to Main content Skip to Navigation
Journal articles

DyKOSMap: A Framework for Mapping Adaptation between Biomedical Knowledge Organization Systems

Abstract : Background. Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. Methods. We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. Results. We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and f-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. Conclusions. The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance.
Document type :
Journal articles
Complete list of metadata
Contributor : Chantal Reynaud Connect in order to contact the contributor
Submitted on : Tuesday, January 5, 2016 - 10:18:21 AM
Last modification on : Thursday, July 8, 2021 - 3:50:31 AM

Links full text



J.C. dos Reis, Cédric Pruski, Marcos da Silveira, Chantal Reynaud-Delaître. DyKOSMap: A Framework for Mapping Adaptation between Biomedical Knowledge Organization Systems. Journal of Biomedical Informatics, Elsevier, 2015, pp.153-173. ⟨10.1016/j.jbi.2015.04.001⟩. ⟨hal-01250647⟩



Les métriques sont temporairement indisponibles