Concept-based information retrieval is known to be a powerful and reliable process. It relies on a semantically annotated corpus, i.e. resources indexed by concepts organized within a domain ontology. The conception and enlargement of such index is a tedious task, which is often a bottleneck due to the lack of (semi-)automated solutions. In this paper, we first introduce a solution to assist experts during the indexing process thanks to semantic annotation propagation. The idea is to let them position the new resource on a semantic map, containing already indexed resources and to propose an indexation of this new resource based on those of its neighbors. To further help users, we then introduce indicators to estimate the robustness of the indexation with respect to the indicated position and to the annotation homogeneity of nearby resources. By computing these values before any interaction, it is possible to visually inform users on their margins of error, therefore reducing the risk of having a non-optimal, thus unsatisfying, annotation.