On Demand ETL of RDB to RDF Mapping for Linked Enterprise Data

Lehireche Nesrine, Malki Mimoun, Lehireche Ahmed and Reda Mohamed Hamou
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Lehireche Nesrine: EEDIS Laboratory, Djillali Liabes, University of University of Sidi Bel-Abbes, University of Sidi Bel-Abbes, Algeria
Malki Mimoun: LABRI-SBA Laboratory, Ecole Supérieure en Informatique de Sidi Bel-Abbes, Algeria
Lehireche Ahmed: EEDIS Laboratory, Djillali Liabes University of Sidi Bel-Abbes, Algeria
Reda Mohamed Hamou: GeCoDe Laboratory, University Tahar Moulay of Saida, Saida, Algeria

International Journal of Strategic Information Technology and Applications (IJSITA), 2017, vol. 8, issue 3, 91-100

Abstract: The purpose of the semantic web goes well beyond a simple provision of raw data: it is a matter of linking data together. This data meshing approach, called linked data (LD), refers to a set of best practices for publishing and interlinking data on the web. Due to its principles, a new context appeared called linked enterprise data (LED). The LED is the application of linked data to the information system of the enterprise to answer all the challenge of an IS, in order to have an agile and performing System. Where internal data sources link to external data, with easy access to information in performing time. This article focuses on using the LED to support the challenges of database integration and state-of-the-art for mapping RDB to RDF based on LD. Then, the authors introduce a proposition for on demand extract transform load (ETL) of RDB to RDF mapping using algorithms. Finally, the authors present a conclusion and discussion for their perspectives to implement the solution.

Date: 2017
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