Ontologies and hierarchical clustering are important tools in biology and medicine to study high-throughput data. Enrichment of ontology terms in the data is used to identify statistically overrepresented ontology terms, giving insight into relevant biological processes or functional modules. Hierarchical clustering is a standard method to analyze data to find relatively homogeneous clusters of experimental data points. Both methods support the analysis of the same data set, but are usually considered independently. This abstract proposes a new visualization method for visualizing a large data set in the context of an ontology under consideration of a clustering of the data.