One of the objectives of the Language Technologies for Life-Long Learning (LTfLL) project, is to develop a knowledge sharing system that connects learners to resources and learners to other learners. To this end, we complement the formal knowledge represented by existing domain ontologies with the informal knowledge emerging from social tagging. More specifically, we crawl data from social media applications such as Delicious, Slideshare and YouTube. Similarity measures are employed to select possible lexicalizations of concepts that are related to the ones present in the given ontology and which are assumed to be socially relevant with respect to the input lexicalisation. In order to identify the appropriate relationships which exist between the extracted related terms and the existing domain ontology, we employ several heuristics that rely on the use of a large background knowledge base, such as DBpedia. An evaluation of the resulting ontology has been carried out. The methodology proposed allows for an appropriate enrichment process and produces a complementary vocabulary to that of a domain expert.