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MongoDB-Based Modular Ontology Building for Big Data Integration

  • Original Article
  • Published:
Journal on Data Semantics

Abstract

Big Data are collections of data sets so large and complex to process using classical database management tools. Their main characteristics are volume, variety and velocity. Although these characteristics accentuate heterogeneity problems, users are always looking for a unified view of the data. Consequently, Big Data integration is a new research area that faces new challenges due to the aforementioned characteristics. Ontologies are widely used in data integration since they represent knowledge as a formal description of a domain of interest. With the advent of Big Data, their implementation faces new challenges due to the volume, variety and velocity dimensions of these data. This paper illustrates an approach to build a modular ontology for Big Data integration that considers the characteristics of big volume, high-speed generation and wide variety of the data. Our approach exploits a NOSQL database, namely MongoDB, and takes advantages of modular ontologies. It follows three main steps: wrapping data sources to MongoDB databases, generating local ontologies and finally composing the local ontologies to get a global one. We equally focus on the implementation of the two last steps.

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Notes

  1. http://dbs.uni-leip-zig.de/en/research/projects/schema_and_ontology_matching/coma_3_0/coma_3_0_community_edition.

  2. http://alignapi.gforge.inria.fr/edoal.html.

  3. http://sioc-project.org/ontology.

  4. http://www.w3.org/TR/owl-features/.

  5. https://www.w3.org/.

  6. http://nosql-database.org/.

  7. http://www.mongodb.org/.

  8. https://www.talend.com/.

  9. https://github.com/raynaldmo/northwind-mongodb.

  10. https://virtuoso.openlinksw.com/dataspace/doc/dav/wiki/Main/VirtRDFViewNorthwindOntology.

  11. https://virtuoso.openlinksw.com/.

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Authors and Affiliations

  1. MIRACL Laboratory, Higher Institute of Computer Science and Multimedia, Sfax University, Sfax, Tunisia

    Hanen Abbes & Faiez Gargouri

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  1. Hanen Abbes
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  2. Faiez Gargouri
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Correspondence to Hanen Abbes.

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Abbes, H., Gargouri, F. MongoDB-Based Modular Ontology Building for Big Data Integration. J Data Semant 7, 1–27 (2018). https://doi.org/10.1007/s13740-017-0081-z

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