Evolution of biomedical ontologies and mappings: Overview of recent approaches <s> Ontology evolution <s> Ontology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to ontology evolution are designed as multiple-stage processes combining techniques from a variety of fields (e.g., natural language processing and reasoning). However, the few existing surveys on this topic lack an in-depth analysis of the various stages of the ontology evolution process. This survey extends the literature by adopting a process-centric view of ontology evolution. Accordingly, we first provide an overall process model synthesized from an overview of the existing models in the literature. Then we survey the major approaches to each of the steps in this process and conclude on future challenges for techniques aiming to solve that particular stage. <s> BIB001 </s> Evolution of biomedical ontologies and mappings: Overview of recent approaches <s> Ontology evolution <s> Objectives: Controlled terminologies and their dependent artefacts provide a consensual understanding of a domain while reducing ambiguities and enabling reasoning. However, the evolution of a domain's knowledge directly impacts these terminologies and generates inconsistencies in the underlying biomedical information systems. In this article, we review existing work addressing the dynamic aspect of terminologies as well as their effects on mappings and semantic annotations. Methods: We investigate approaches related to the identification, characterization and propagation of changes in terminologies, mappings and semantic annotations including techniques to update their content. Results and conclusion: Based on the explored issues and existing methods, we outline open research challenges requiring investigation in the near future. <s> BIB002
The life sciences are a highly dynamic domain by nature. New findings lead to a constant renewal of domain knowledge making it richer over time. However, this evolution deeply impacts domain ontologies, forcing experts to regularly revise their content. Ontology evolution is therefore a research field that has gained more and more interest over the past years through a joint effort of the biomedical and Semantic Web communities. Since this subject has been recently surveyed  BIB001 BIB002 , we focus on pointing out some interesting novel investigations, that are or will be particularly important to improve the adaptation process for ontology-based mappings and applications. This covers ontology change detection, the visualization of ontology evolution and ontology change prediction and tracking. Further challenges will be discussed in Section 5.