Big Data and Doctoral Research: Opportunities, Challenges, and Cautions

Big Data and Doctoral Research: Opportunities, Challenges, and Cautions

Richard C. Berry (Intersect Australia, Australia) and Lucy Johnston (University of Newcastle, Australia)
Copyright: © 2019 |Pages: 17
DOI: 10.4018/978-1-5225-7065-3.ch004

Abstract

This chapter explores opportunities and challenges that are presented to doctoral candidates (and indeed all researchers) through access to big data. The authors consider what big data is and what it is not, and how working with big data differs from traditional research design and analysis. They provide examples of the opportunities that big data offers in terms of the combination of diverse data sets, sources, and types and how it can provide new perspectives on inter-disciplinary challenges. They also highlight some of the challenges for the use of big data, both for the individual researcher and for institutions. The authors advocate for the need to embrace these challenges but without foregoing data integrity and the expert use and interpretation of data.
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Defining Big Data

In considering Big Data and its potential impact on doctoral (and indeed other) research, it is important to begin with a clear definition of what Big Data is, what it is not, and importantly to clarify the distinction between large datasets and Big Data.

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