We can observe that the amount of non-toy domain ontologies is stillvery limited for many areas of interest. In contrast, folksonomies are widely inuse for (1) tagging Web pages (e.g. del.icio.us), (2) annotating pictures (e.g.flickr), or (3) classifying scholarly publications (e.g. bibsonomy). However,such folksonomies cannot offer the expressivity of ontologies, and therespective tags often lack a context-independent and intersubjective definitionof meaning. Also, folksonomies and other unsupervised vocabularies frequentlysuffer from inconsistencies and redundancies. In this paper, we argue that thesocial interaction manifested in folksonomies and in their usage should beexploited for building and maintaining ontologies. Then, we sketch acomprehensive approach for deriving ontologies from folksonomies byintegrating multiple resources and techniques. In detail, we suggest combining(1) the statistical analysis of folksonomies, associated usage data, and theirimplicit social networks, (2) online lexical resources like dictionaries, Wordnet,Google and Wikipedia, (3) ontologies and Semantic Web resources, (4)ontology mapping and matching approaches, and (5) functionality that helpshuman actors in achieving and maintaining consensus over ontology elementsuggestions resulting from the preceding steps.