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An important aspect when generating microtasks from RDF data (or machine-readable data in general) is developing useful human-understandable interfaces (Algorithm 1, line 9) for the target non-expert crowds. In microtasks, optimal user interfaces reduce ambiguity as well as the probability to retrieve erroneous answers from the crowd due to a misinterpretation of the task. Therefore, before start to resolve one of our tasks, the crowd workers were instructed with details and examples about each quality issue. After reading the instructions, workers proceed to resolve the given task. Figure 3 depicts the interface of a microtask generated for the Find stage in our approach. To display each triple, we retrieved the values of the foaf:name or rdfs:label properties for subjects, predicates, and datatypes. The name of languages in language-tagged strings were parsed using a conversion table from the best current practices BCP 47 [7], as suggested by the RDF specification 7 . Language tags and datatypes of objects were highlighted, such that workers can easily identify them [Footnote 8] . Additionally, in order to provide contextual information, we implemented a simple wrapper which extracts the corresponding data encoded in the infobox of the Wikipedia article associated with the resource – specified via foaf:isPrimaryTopicOf . The crowd has the possibility to select one or several quality issues per triple.
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