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Metadata driven integration model for large scale data integration

The emergence of large scale systems provides solutions and poses new challenges to a number of existing problems covering a broad spectrum of applications. Among these problems, we are interested by exploring new approaches to integrate data in large scale systems. For this purpose, we propose a data integration framework that is data-structure-independent, allowing a high level of semantic interoperability. We describe the methods used in our framework to build an index regrouping all the clusters published data descriptions that are designed to fit the structure of a large scale system. This framework focuses on the properties of large scale systems such as multi-level heterogeneity and high degree of dynamicity and evolution.