In this paper, a methodology is presented that aids in finding equivalent terms between semantically similar controlled vocabularies. It is based both on lexical similarities discovery and semantic alignment through external LOD datasets. The proposed methodology has been deployed for the identification of equivalent terms within two datasets consisting of subject headings, namely Dione and NYT and facilitated through the employment of the LOD datasets of DBpedia and WordNet. The effectiveness of the methodology is assessed through a comparative evaluation between the deployment of the methodology presented in this paper and the deployment of a lexical similarities-based algorithm presented in previous work.