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Ontologies can support a variety of purposes,\udranging from capturing the conceptual knowledge\udto the organisation of digital content and information.\udHowever, information systems are always subject to\udchange and ontology change management can pose challenges.\udIn this sense, the application and representation\udof ontology changes in terms of higher-level change operations\udcan describe more meaningful semantics behind\udthe applied change. In this paper, we propose a\udfourphase process that covers the operationalization,\udrepresentation and detection of higherlevel changes in\udontology evolution life cycle. We present different levels\udof change operators based on the granularity and\uddomainspecificity of changes. The first layer is based on\udgeneric atomic level change operators, whereas the next\udtwo layers are user-defined (generic/domainspecific) change\udpatterns. We introduce layered change logs for the explicit operational representation of ontology changes.\udWe formalised the change log using a graph-based approach.\udWe introduce a technique to identify composite\udchanges that not only assists in formulating ontology\udchange log data in a more concise manner, but\udalso helps in realizing the semantics and intent behind\udany applied change. Furthermore, we identify frequent\udchange sequences that are applied as a reference in order\udto discover reusable, often domainspecific and usagedriven\udchange patterns. We describe the pattern identification\udalgorithms and evaluate their performance

Ontology Change Management and Identification of Change Patterns