BibSonomy ::  publication ::

We can observe that the amount of non-toy domain ontologies is still very limited for many areas of interest. In contrast, folksonomies are widely in use 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 folksonominies cannot offer the expressivity of ontologies, and the respective tags often lack a context-independent and intersubjective definition of meaning. Also, folksonomies and other unsupervised vocabularies frequently suffer from inconsistencies, redundancies and uncontrolled growth. In this paper, we argue that the social interaction manifested in folksonomies and in their usage should be exploited for building and maintaining ontologies. Then, we sketch a comprehensive approach for deriving ontologies from folksonomies by integrating multiple resources and techniques. In detail, we suggest combining 1 the statistical analysis of folksonomies, associated usage data, and their implicit social networks, 2 Web resources like Google, Wikipedia, and the Leo dictionaries; 3 WordNet and other terminological resources, 4 ontology mapping and matching approaches, and 5 functionality that helps human actors in achieving and maintaining consensus over ontology element suggestions resulting from the preceeding steps.