Automatic maintenance of semantic annotations
Abstract
Biomedical Knowledge Organization Systems (KOS) play a key role in enriching information in order to make them machine understandable. This is done through semantic annotation which consists in the association of concept labels taken from KOS with pieces of digital information taken from the source to annotate. However, the dynamic nature of these KOS directly impacts on the annotations, creating a mismatch between the enriched data and the concept labels. This PhD study addresses the evolution of semantic annotations due to the evolution of KOS and aims at proposing an approach to automatize the maintenance of semantic annotations.