This paper deals with the problem of maintenance of semantic annotations produced based on domain ontologies. Many annotated texts have been produced and made available to end-users. If not reviewed regularly, the quality of these annotations tends to decrease over time due to the evolution of the domain ontologies. The quality of these annotations is critical for tools that exploit them e.g., search engines and decision support systems and need to ensure an acceptable level of performance. Although the recent advances for ontology-based annotation systems to annotate new documents, the maintenance of existing annotations remains under studied. In this work we present an analysis of the impact of ontology evolution on existing annotations. To do so, we used two well-known annotators to generate more than 66 million annotations from a pre-selected set of 5000 biomedical journal articles and standard ontologies covering a period ranging from 2004 to 2016. We highlight the correlation between changes in the ontologies and changes in the annotations and we discuss the necessity to improve existing annotation formalisms in order to include elements required to support semi- automatic annotation maintenance mechanisms. Evolution of Semantic Annotations ELISA INSPIRATION: The efficient management and exploitation of digital information is pushing companies to rely on Semantic Web technologies. Ontologies offer the means to make the semantics of data explicit by annotating available data with concept labels that make it possible for machines to understand the annotated data. This is the case, for instance, in the health sector where patient data stored in electronic health records (EHRs) are associated with concept codes or terms borrowed from standard controlled terminologies such as the International Classification of Diseases (ICD) or SNOMED CT, facilitating data exchange between health professionals. However, the dynamic nature of domain knowledge forces engineers to revise the content of ontologies, creating a mismatch between the definition of concepts and the annotations, thus preventing any intelligent exploitation of the data. INNOVATION: In this context, and in direct line with the results of the DynaMO project, ELISA will develop innovative concepts and tools to: Understand and characterize the evolution of ontologies over time with respect to the problem of semantic annotation evolution, Maintain the semantic annotations impacted by the evolution of ontologies they derived from. Two cases will be distinguished: A direct modification if the annotations are modifiable, An ad-hoc modification if the annotations are not accessible. This will be done through the design of a query enrichment mechanism reflecting the evolution of ontology in order to keep annotated data searchable over time. IMPACT: The proposed technology will help companies in managing the ever-increasing quantity of data they have to deal with. Moreover, it will be implemented in two real cases borrowed from the field of life sciences. First, we plan to apply our maintenance approach to annotations that serve to enrich patient data in the Luxembourgish national health platform. Second, we will investigate the semantic annotation maintenance problem that arises from the annotation of Case Report Forms used in clinical trial research.