An Automatic Generation of Domain Ontologies Based on an MDA Approach to Support Big Data Analytics

An Automatic Generation of Domain Ontologies Based on an MDA Approach to Support Big Data Analytics

Naziha Laaz, Karzan Wakil, Sara Gotti, Zineb Gotti, Samir Mbarki
Copyright: © 2021 |Pages: 20
DOI: 10.4018/978-1-7998-3661-2.ch002
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Abstract

This chapter proposes a new methodology for the automatic generation of domain ontologies to support big data analytics. This method ensures the recommendations of the MDA approach by transforming UML class diagrams to domain ontologies in PSM level through ODM, which is an OMG standard for ontology modeling. In this work, the authors have focused on the model-driven architecture approach as the best solution for representing and generating ontology artifacts in an intuitive way using the UML graphical syntax. The creation of domain ontologies will form the basis for application developers to target business professional context; however, the future of big data will depend on the use of technologies to model ontologies. With that said, this work supports the combination of ontologies and big data approaches as the most efficient way to store, extract, and analyze data. It is shown using the theoretical approach and concrete results obtained after applying the proposed process to an e-learning domain ontology.
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Context

The background of this work is presented under different subsections. Each of these subsections discuss the foundations of our proposal. In particular, Section II.A gives an overview of big data and its recognized, inherent characteristics. Also, we cite several advantages of the use of ontologies in a big data area. In section II-B, we define domain ontologies. For the last part in this section, we present and describe model-driven engineering and its standards used in this work UML and ODM, respectively.

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