During the last decades, the Data Warehouse has been one of the main components of a Decision Support System (DSS) inside a company. Given the great diffusion of Data Warehouses nowadays, managers have realized that there is a great potential in combining information coming from multiple information sources, like heterogeneous Data Warehouses from companies operating in the same sector. Existing solutions rely mostly on the Extract-Transform-Load (ETL) approach, a costly and complex process. The process of Data Warehous integration can be greatly simplified by developing a method that is able to semi-automatically discover semantic relationships among attributes of two or more different, heterogeneous Data Warehouse schemas. In this paper, we propose a method for the semi-automatic discovery of mappings between dimension hierarchies of heterogeneous Data Warehouses. Our approach exploits techniques from the Data Integration research area by combining topological properties of dimensions and semantic techniques.