Providing Clarity on Big Data Technologies
| Autor: | Daniel Staegemann, Matthias Volk, Matthias Pohl, Naoum Jamous, Klaus Turowski |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Big data 02 engineering and technology Artifact (software development) Design science Ontology (information science) computer.software_genre Popularity Data science Ontology engineering law.invention law 020204 information systems 0202 electrical engineering electronic engineering information engineering CLARITY Selection (linguistics) 020201 artificial intelligence & image processing Decision Sciences (miscellaneous) business computer Information Systems |
| Zdroj: | International Journal of Intelligent Information Technologies. 16:49-73 |
| ISSN: | 1548-3665 1548-3657 |
| DOI: | 10.4018/ijiit.2020040103 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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