| Issue |
EPJ Web Conf.
Volume 224, 2019
IV International Conference “Modeling of Nonlinear Processes and Systems” (MNPS-2019)
|
|
|---|---|---|
| Article Number | 04011 | |
| Number of page(s) | 4 | |
| Section | Machine Learning, Artificial Intelligence and High-Performance Computing | |
| DOI | https://doi.org/10.1051/epjconf/201922404011 | |
| Published online | 09 December 2019 | |
https://doi.org/10.1051/epjconf/201922404011
On Definition of BigData
1
Murmansk Arctic State University, Near-Earth Environment Computer Modelling Laboratory, RU-183025, Murmansk, Russia
2
Murmansk State Technical University, Department of Math, Information Systems and Software Engineering, RU-183010, Murmansk, Russia
* e-mail: ZolotovO@gmail.com
Published online: 9 December 2019
The term Big Data (or BigData) is widely used in scientific, educational, and business literature; however, there does not exist a single definition that can be unreservedly called “canonical”. A careless use of Big Data term to promote commercial software further emphasizes the importance of this issue. In this paper, we have performed a review of definitions of Big Data and highlighted the principal features that are attributed to Big Data. We compared all these principal features with features of databases compiled using Edgar F. Codd’s publications, and showed that they are not unique and can also be attributed to the databases. Having studied C. Lynch original work, we proposed the definition of Big Data based on the so-called conservation institution. The key point of this definition is a shift from purely technical attitude towards public institutions. Since the current use of the Big Data term may lead to a loss of meaning. There is a need not only to spread out best practices but also to eliminate or minimize the use of dubious or misleading ones.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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