Providing Clarity on Big Data Technologies: The BDTOnto Ontology

Matthias Volk, Daniel Staegemann, Naoum Jamous, Matthias Pohl and Klaus Turowski
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Matthias Volk: Otto-von-Guericke University Magdeburg, Germany
Daniel Staegemann: Otto-von-Guericke University Magdeburg, Germany
Naoum Jamous: Otto-von-Guericke University Magdeburg, Germany
Matthias Pohl: Otto-von-Guericke University Magdeburg, Germany
Klaus Turowski: Otto-von-Guericke University Magdeburg, Germany

International Journal of Intelligent Information Technologies (IJIIT), 2020, vol. 16, issue 2, 49-73

Abstract: Big Data is a term that gained popularity due to its potential benefits in various fields, and is progressively being used. However, there are still many gaps and challenges to overcome, especially when it comes to the selection and handling of relevant technologies. A consequence of the huge number of manifestations in this area, growing each year, the uncertainty and complexity increase. The lack of a classification approach causes a growing demand for more experts with a broad knowledge and expertise. Using various techniques of ontology engineering and following the design science methodology, this work proposes the Big Data Technology Ontology (BDTOnto) as a comprehensive and sustainable classification approach to classify big data technologies and their manifestations. In particular, a reusable, extensible and adaptable artifact in the form of an ontology will be developed and evaluated.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jiit00:v:16:y:2020:i:2:p:49-73

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