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

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

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) and Reda Mohamed Hamou (GeCoDe Laboratory, University Tahar Moulay of Saida, Saida, Algeria)
Copyright: © 2017 |Pages: 10
DOI: 10.4018/IJSITA.2017070106
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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.
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Basic Concepts

This section is reserved for the introduction of some basic concepts that we are going to use in our approach.

Linked Data

Linked Data is about using the Web to create typed links between data from different sources. These may be as diverse as databases maintained by the two organizations in different geographical locations, or simply heterogeneous systems within one organization that, historically, have not easily interoperated at the data level. Technically, Linked Data refers to data published on the Web in such a way that it is machine-readable, its meaning is explicitly defined, it is linked to other external data sets, and can in turn be linked to from external data sets (Bizer, 2012).

Berners-Lee (2006) outlined a set of 'rules' for publishing data on the Web in a way that all published data become part of a single global data space:

  • 1.

    Use URIs as names for things

  • 2.

    Use HTTP URIs so that people can look up those names

  • 3.

    When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL)

  • 4.

    Include links to other URIs, so that they can discover more things

These have become known as the 'Linked Data principles'; and provide a basic recipe for publishing, and connecting data, using the infrastructure of the Web while adhering to its architecture and standards (see Figure 1).

Figure 1.

Example RDF links

IJSITA.2017070106.f01

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