Traditional subject indexing and classification are considered infeasible in many digital collections. Automated means and social tagging are often suggested as the two possible solutions. Both, however, have disadvantages and, depending on the purpose of use or context, require additional manual input. This study investigates ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Benefits of using both social tags and controlled terms are also explored, including enriching knowledge organization systems with new concepts.