.png)
.png)
Email this article 
Big Data as a phenomenon of social philosophy and professional education
https://doi.org/10.15372/PEMW20180405
Abstract
In this paper we discuss the social philosophical and educational aspects of Big Data. Coined as a term for the mechanism of collecting, storing, and processing huge amounts of data, Big Data has lead to visible shifts in scientific research and the understanding that there is now a novel culture of information and communication technology. We discuss the processes of gathering Big Data and its affect on all areas of social development, including research and fi One of the applications of this technology is in the sphere of higher education; a function, forecasting Big Data development has been determined and is discussed in the following paper. A vivid example of using this technology in the process of university teaching and research is given based on a novel interdisciplinary project of Reshetnev Siberian State University of Science and Technology (Krasnoyarsk, Russia). This project is aimed at building a geographical information system on the basis of large amounts of geographical data collected by remote sensing equipment.
About the Authors
S. Yu. PiskorskayaRussian Federation
Svetlana Yu. Piskorskaya – Doctor of Philosophy, Director of the Institute of Social Engineering
660037, Krasnoyarsk, prospekt imeni gazety ‘Krasnoyarskii rabochii`, 31
A. E. Goncharov
Russian Federation
Aleksandr E. Goncharov – Cand.Sc. in history, docent Department of Technical Foreign Languages
660037, Krasnoyarsk, prospekt imeni gazety ‘Krasnoyarskii rabochii`, 31
References
1. Guseva A.A. [«Big Data»: the basic principles, sources, and capabilities], Masters Journal, 2016, no 1, pp. 320–324. (In Russ.)
2. Forming a knowledge-based society. New tasks of higher education: a report of the World Bank. Moscow, Ves mir, 2003, 232 p.
3. Maier-Shenberger V., Kukier K. Big Data. The revolution that will change the way we live, work, and think. Мoscow, Mann, Ivanov, and Ferber, 2014, 240 p.
4. Kravets A. S. Nature and probability (philosophical aspects). Moscow: Mysl’, 1976, 173 p.
5. Big Data for state management. Available at: http://ac.gov.ru/files/content/10087/pushkin-bolshie-dannye-dlya-gosupravleniya-pdf.pdf (accessed August 15, 2018).
6. Nazarova M.A., Chernykh S. I. [Transformation of identity in society]. Professional education in the modern world, 2017, vol. 7, no. 3, pp. 1163–1168. (In Russ.)
7. Tsymbler M. L. [Big Data: a few simple questions about the complex]. Superkomp’iutery, 2014, no. 1 (17), pp. 8–11. (In Russ.)
8. What is Big Data in marketing: problems, algorithms, and methods of analysis. Available at: https:// lpgenerator.ru/blog/2015/11/17/chto-takoe-big-data-bolshie-dannye-v-marketinge-problemy-algoritmy-metody-analiza/ (accessed August 15, 2018)
9. Khalilov D. 98 targeting parameters on Facebook. Available at: http://madcats.ru/smm/98-facebook-targetings/ (accessed August 15, 2018).
10. Chekharin E. E. [Big Data – big problems]. Perspektivy nauki i obrazovaniia. 2016, no. 3 (21), pp. 7–11. (In Russ.)
11. Drozdova A.A. [Big Data for education: a study of persectives]. Molodoi issledovatel’ Dona. 2016, no 2 (2). Available at: http://mid-journal.ru/upload/iblock/6a4/drozdova.pdf (accessed August 14, 2018).
12. Mikhnev I. P., Chelnokova A. D., Reut A. D. [The technology of Big Data and its application in modern higher education]. Razvitie sovremennogo obrazovaniia: ot teorii k praktike – Conference Proceedings. Cheboksary: Interaktiv plius, 2018. Available at: https://interactive-plus.ru/e-articles/527/Action527–470090.pdf (accessed August 14, 2018).
13. Pfanenshtil I.A., Yatsenko M. P. [Informational aspects of management education]. Professional education in the modern world, 2018. vol. 8, no. 1, pp. 1581–1586. (In Russ.)
14. Big Data in higher education: a special project. Available at: http://imguu.ru/nauchnaya-rabota/bigdata/ (accessed August 16, 2018).
15. Katsko S. Iu. Big Data for geographical information system spaces for effective management during situations of crisis. Available at: https://cyberleninka.ru/article/n/bolshie-dannye-v-geoinformatsionnom-prostranstve-dlya-effektivnogo-upravleniya-v-krizisnyh-situatsiyah (accessed August 18, 2018).
16. Blondel P. The handbook of sidescan sonar. Chichester (UK): Spinger – Praxis Publ. Ltd., 2009, 316 p.
17. U. S. Geological Survey Scientific Investigations Report 2007–5012 URL: https://pubs.usgs.gov/ sir/2007/5012/section3.html (accessed October 18, 2018).
18. Kaeser A. J., Litts T. L., Tracy T. W. Using low-cost side-scan sonar for benthic mapping throughout the Lower Flint River, Georgia, USA. River Research and Applications, 2013, no. 29 (5), pp. 634–644.
19. Van Der Wal D., Pye K. The use of historical bathymetric charts in a GIS to assess morphological change in estuaries. The Geographical Journal, 2003, vol. 169 (1), pp. 21–31.
20. O’Shea J. M. The identification of shipwreck sites: a Bayesian approach. Journal of Archeological Science, 2004, no. 31, pp. 1533–1552.
21. Malakoff D. Bayes offers a ‘new’ way to make sense of numbers. Science, 1999, vol. 286 (5444), pp. 1460–1464.
Supplementary files
For citation: Piskorskaya S.Y., Goncharov A.E. Big Data as a phenomenon of social philosophy and professional education. Professional education in the modern world. 2018;8(4):2178-2185. https://doi.org/10.15372/PEMW20180405
Refbacks
- There are currently no refbacks.
