In Proceedings of the 14th International Semantic Web Conference: Posters and Demos (2015)
Obtaining Linked Data by modeling domain-level knowledge derived from input data is not straightforward for data publishers, especially if they are not Semantic Web experts. Developing user interfaces that support domain experts to semantically annotate their data became feasible, as the mapping rules were abstracted from their execution. However, most existing approaches reflect how mappings are typically executed: they offer a single linear workflow, triggered by a particular data source. Alternative approaches were neither thoroughly investigated yet, nor incorporated in most existing user interfaces for mappings. In this paper, we generalize the two prevalent approaches for generating mappings of data in databases: database-driven and ontology-driven, to be applicable for any other data structure; and introduce two approaches: model-driven and result-driven.