Spreadsheets are widely used by knowledge workers, especially in the industrial sector. Their methodology enables a well understood, easy and fast possibility to enter data. As filling out a spreadsheet is more accessible to common knowledge workers than defining RDF statements, in this paper, we propose an easy-to-use, zero-configuration, web-based spreadsheet editor that simultaneously transfers spreadsheet entries into RDF statements. It enables various kinds of users to easily create semantic data whether they are RDF experts or novices. The typical scenario we address focuses on creating instance data starting with an empty knowledge base that is filled incrementally. In a user study, participants were able to create more statements in shorter time, having similar or even significantly outperforming quality, compared to other approaches.
Pohl @cite_4 published , a web-based tool to create RDF data that could also be used by Semantic Web laymen. Using a subject-predicate-object table, users were able to enter labels which were mapped to URIs using the now discontinued Semantic Web search engine Sindice. Auto completion of already loaded concepts was also possible.
@cite_4
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rdfedit is a web application running on Django, rdflib and jQuery DataTables that supports novices in the field of Semantic Web technologies with the creation of RDF instance metadata. By utilizing the Semantic Web search engine Sindice, rdfedit can transform literals into URIs, fetch triples from external resources and import them into the user’s local graph. Metadata experts can easily configure these features of rdfedit to fit their preferences regarding metadata schemata, so metadata creators with few knowledge about Semantic Web technologies can create RDF data in a fast and consistent manner while also following the Linked Data principles.