Schema mapping is a challenging problem. It has come to the fore in recent years; there are important applications like database schema integration and, more recently, digital library merging of heterogeneous data. Previous studies have approached the schema mapping process either from algorithmic or visualization perspectives, with few integrating both. With Schema Mapper we demonstrate a semi-automatic tool for schema integration that combines a novel visual interface with an algorithm-based recommendation engine. Schemas are visualized as hyperbolic trees, thus allowing more schema nodes to be displayed at one time. Matches to selections are recommended to the user, which makes the mapping operation easier and faster