An Ontology-Matching Based Proposal to Detect Potential Redundancies on Enterprise Architectures

Our work presents an approach to automatic detection of potentially redundant elements within an Enterprise Architecture (EA). Unintended or unidentified redundancies can affect the data quality, duplicating efforts which may lead to inconsistencies. Evaluating and identifying manually redundant elements in large information systems (IS) is a tedious, error-prone and time-consuming task. Untimely, incomplete or inaccurate analysis, could affect the dynamics and organizational flexibility that promotes an EA. Our proposal is a MDA (Model-Driven Architecture) and Ontology-Alignment based. The main idea is to perform a transformation from an EA model towards ontology in OWL format (Ontology Web Language) and exploit ontology matching tools to infer correspondences between concepts. Our objective is to support analysis and making decisions of architect with an integral view which describes EAs data and processes, and its inner relationships.