Model-driven Integration Architecture to Overcome Data Complexity Why we Need Rational Approaches to Face Miscellaneous Issues

Integration of data resources is widely used by organizations involved in competitive, high-value-added domains. Various solutions are developed to deal with integration issues even if they lack rational methods to face emerging complexity due to semantic connectedness of data sources, especially in Life Sciences and Health. To get credible and best valuable output , needs and solutions must be formalized as a set of unambiguous statements telling “Which”, “When”, “For what” and “How” data integration is designed and implemented. Model-driven approaches were found to achieve these requirements. In this paper, modeldriven data integration was put in perspectives in the context of current approaches with special attention to semantic complexity.