Description

The current wealth of information, typically known as Big Data, generates a large amount of available data sources. Data Integration provides foundations to query disparate data sources as if they were integrated into a single source. However, the heterogeneous nature of these sources represent a challenge to traditional data integration. To enable data integration of highly heterogeneous and disparate data sources, this paper presents a method to extract the schema from semi-structured (such as JSON and XML) and structured (such as relational) data sources, and generate an equivalent RDFS representation. The output of our method facilitates data integration as all data sources are represented with a single canonical data model. Relevantly, our approach consists of production rules at the meta-model level that guarantee the correctness of the model translations. Finally, a tool implementing our approach has been developed.

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