Designing and refining ontologies becomes a tedious task, once the boundary to real-world-size knowledge bases has been crossed. Hence semi-automatic methods supporting those tasks will determine the future success of ontologies in practice. Our research therefore aims at the conceptual development and implementation of tools for semi-automatic ontology engineering. By combining Ontology Learning and Relational Exploration we hope to overcome the knowledge acquisition bottleneck, especially with respect to expressive axiomatizations (see our seminal paper at ICCS'2007). The RELExO framework supporting the refinement and evaluation of OWL DL ontologies is open source and publicly available under the LGPL license.