The potential of Linked Open Data (LOD) about cultural artifacts in the Humanities and Social Sciences (SSH) can only be realized if effectively interwoven with existing content in the Semantic Web. This project data-mines the LOD Laundromat dataset, billions of triples from the huge LOD knowledge graph. Digging into the Knowledge Graph identifies, evaluates and indexes SSH vocabularies by mapping clusters of similar meaning onto Knowledge Organization Systems (KOSs). The project provides insights into LOD vocabularies for SSH open data production; how evolving KOSs reflect and serve the LOD cloud, especially interdisciplinarity. Musicology and economics use cases inform the design of a Linked Data workflow in SSH projects. By indexing the LOD cloud this research will enhance researchers’ ability to search the Semantic Web and contribute to it, but also the ability of trusted digital repositories to archive Linked Data, including unique and thereby possibly endangered vocabularies.