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Many aspects of linked data management - including exposing legacy data and applications to semantic formats, designing vocabularies to describe RDF data, identifying links between entities, query processing, and data curation - are necessarily tackled through the combination of human effort with algorithmic techniques. In the literature on traditional data management the theoretical and technical groundwork to realize and manage such combinations is being established. In this paper, the authors build upon and extend these ideas to propose a framework by which human and computational intelligence can co-exist by augmenting existing linked data and linked service technology with crowdsourcing functionality.
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