Ontology evolution is an intrinsic phenomenon of any knowledge-intensive
system, which can be addressed either implicitly or explicitly.
This paper describes an approach to capture and visualize implicit
data-driven ontology evolution using ontologies semi-automatically
generated by extending small seed ontologies.
This process captures ontology changes reflected in large document
collections. Visualizing of these changes helps characterize the
evolution process, and distinguish core, extended and peripheral relations
between concepts. Finally, the paper presents an example of ontology
evolution by monitoring and analyzing online media coverage on ``energy
sources'' over a period of ten months.
Keywords: data-driven changes, ontology evolution, ontology extension, ontology learning