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A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques

A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques

Madhavi Arun Vaidya, Meghana Sanjeeva
Copyright: © 2021 |Pages: 20
ISBN13: 9781799834762|ISBN10: 179983476X|EISBN13: 9781799834779
DOI: 10.4018/978-1-7998-3476-2.ch004
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MLA

Vaidya, Madhavi Arun, and Meghana Sanjeeva. "A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques." Handbook of Research on Modern Educational Technologies, Applications, and Management, edited by Mehdi Khosrow-Pour D.B.A., IGI Global, 2021, pp. 48-67. https://doi.org/10.4018/978-1-7998-3476-2.ch004

APA

Vaidya, M. A. & Sanjeeva, M. (2021). A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques. In M. Khosrow-Pour D.B.A. (Ed.), Handbook of Research on Modern Educational Technologies, Applications, and Management (pp. 48-67). IGI Global. https://doi.org/10.4018/978-1-7998-3476-2.ch004

Chicago

Vaidya, Madhavi Arun, and Meghana Sanjeeva. "A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques." In Handbook of Research on Modern Educational Technologies, Applications, and Management, edited by Mehdi Khosrow-Pour D.B.A., 48-67. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-3476-2.ch004

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Abstract

Research, which is an integral part of higher education, is undergoing a metamorphosis. Researchers across disciplines are increasingly utilizing electronic tools to collect, analyze, and organize data. This “data deluge” creates a need to develop policies, infrastructures, and services in organisations, with the objective of assisting researchers in creating, collecting, manipulating, analysing, transporting, storing, and preserving datasets. Research is now conducted in the digital realm, with researchers generating and exchanging data among themselves. Research data management in context with library data could also be treated as big data without doubt due its properties of large volume, high velocity, and obvious variety. To sum up, it can be said that big datasets need to be more useful, visible, and accessible. With new and powerful analytics of big data, such as information visualization tools, researchers can look at data in new ways and mine it for information they intend to have.

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