alexa Teaching Data Science and Cloud Computing in Low and Middle Income Countries
ISSN: 2379-1764

Advanced Techniques in Biology & Medicine
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Review Article

Teaching Data Science and Cloud Computing in Low and Middle Income Countries

Hugh Shanahan1, Andrew Harrison2 and Sean Tobias May3*
1Department of Computer Science, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, United Kingdom
2Department of Mathematical Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom
3School of Biosciences, University of Nottingham, Sutton Bonington, Loughborough LE12 5RD, United Kingdom
Corresponding Author : Sean Tobias May
School of Biosciences, University of Nottingham
Sutton Bonington, Loughborough LE12 5RD, United Kingdom
Tel: +4407801568910
E-mail: [email protected] arabidopsis.info
Received: September 21, 2015; Accepted: November 16, 2015; Published: November 23, 2015
Citation: Shanahan H, Harrison A, May ST (2015) Teaching Data Science and Cloud Computing in Low and Middle Income Countries. Adv Tech Biol Med 3:150. doi:10.4172/2379-1764.1000150
Copyright: © 2015 Shanahan H, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Abstract

Large, publicly available data sets present a challenge and an opportunity for researchers based in Low and Middle Income Countries (LMIC). The challenge for these researchers is how they can make use of such data sets given their poor connectivity and infrastructure. The opportunity is the ability to perform leading edge research using these data sets and hence avoid having to invest substantial resources in generating the data sets. The offshoot of this will be to generate solutions to the substantial local problems encountered in these countries and create an educated workforce in data science. Cloud computing in particular may well close the infrastructural gap here. In this paper we discuss our experiences of teaching a variety of summer schools on data intensive analysis in bioinformatics in China, Namibia and Malaysia. On the basis of these experiences we propose that a larger series of summer schools in data science and cloud computing in LMIC would create a cadre of data scientists to start this process. We finally discuss the possibility of the provision of cloud computing resources where the usage costs are controlled so that it is affordable for LMIC researchers.

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