Information semantics and semantic interoperability among applications, systems, and services are mostly based on ontology. Its increase usage in Information Systems and Knowledge Sharing Systems raises the importance of ontology maintenance. Ontology change management incorporates areas like ontology engineering, evolution versioning, merging, integration, and maintenance. Changes are made to the body of knowledge as experts develop a better understanding of the domain. As a result, the body of knowledge evolves from one state to another. Preserving consistency, while accommodating new changes, is a crucial task that needs special attention. This paper aims at providing a comprehensive review on key approaches followed in the field of ontology evolution. The analysis reveals that different individual components have been developed but a complete integrated system for automated ontology evolution is not available yet. This paper introduces some unfolded challenges in the field of ontology evolution, which must be tackled to complete the process automatically. Moreover, the new changes could affect the dependent data, applications, systems, and services. Therefore, this paper also discusses in detail why special attention must be paid to minimize the after effects of ontology evolution and proposes some possible solutions to achieve this goal.