A sketch-based conceptual level data integration methodology

Nowadays, enterprises often need to integrate heterogeneous data sources for many purposes. Given the inherent complexity of this process, several solutions based on visual manipulation paradigms have been proposed to shoot at the complexity of low-level data integration activities. However, when dealing with complex data sources the use of visual notations might suffer from scale-up problems. One way to solve this problem is to raise the data integration activity at more an abstract level. In this paper, we present a methodology for reconciling data sources at the level of their conceptual Schemas. The methodology provides a sketch-based language for manipulating conceptual Schemas, a tool prototype, and logic based inference mechanisms to handle lower level schema integration, metadata generation, and loading of data from sources to the reconciled database. We also provide a usability study to prove the effectiveness of the proposed methodology.