Detección de Elementos Redundantes en Arquitecturas de Información: Un Enfoque Apoyado en Alineación de Ontologı́as

Resumen

This paper proposes an approach for the detection of potentially redundant elements within Enterprise Architectures (EA). Unintended or unidentified redundancies affect the data quality, promote duplication and may lead to inconsistencies. Evaluating and identifying manually redundant elements in large information systems is a tedious, error-prone, and time-consuming task. Untimely, incomplete or inaccurate evaluations, can affect the dynamics and flexibility organizational that promotes an EA. Our proposal is MDA (Model-Driven Architecture) and Ontology-Alignment based. The main idea is to perform a transformation from an information architecture model toward an OWL (Ontology Web Language) ontology, and to apply alignment techniques to infer correspondences between ontology concepts. Our intention in this paper is to support the information architecture, warning to architect about possible overlapping of entity, attribute and association, in order to support assessment, migration, refinement, integration and management processes of enterprise data schemes.