The ever-increasing quantity of data produced in biomedical applications requires the development of intelligent tools implementing Knowledge Organization Systems (KOS) like ontologies, thesauri, or classification schemes for a better integration and exploitation of this data. However, due to the size of this application field, element overlapping can occur between different KOS relying on various knowledge representation models. Therefore, mappings are necessary to improve the semantic interoperability of systems using KOS. Moreover, due to the dynamics of the biomedical domain, KOS constantly evolve over time, and new versions are released periodically forcing domain experts to revise the existing mappings affected by the evolution of the underlying heterogeneous KOS. In this paper, we provide an analysis of the mapping evolution problem. We highlight the lacks of existing approaches to deal with this problem and outline the sketch of the DyKOSMap framework as a prospective solution.