The explosion of biomedical data and the growing number of disparate data sources are exposing researchers to a new challenge - how to acquire, maintain and share knowledge from large and distributed databases in the context of rapidly evolving research. This paper describes research in progress on a new methodology for leveraging the semantic content of ontologies to improve knowledge discovery in complex and dynamic domains. It aims to build a multi-dimensional ontology able to share knowledge from different experiments undertaken across aligned research communities in order to connect areas of science seemingly unrelated to the area of immediate interest. We analyze how ontologies and data mining may facilitate biomedical data analysis and present our efforts to bridge the two fields, knowledge discovery in Biomedicine, and ontology learning for successful data mining in large databases. In particular we present an initial biomedical ontology case study and how we are integrating that with a data mining environment
