Mann, RP orcid.org/0000-0003-0701-1274 and Woolley-Meza, O (2017) Maintaining intellectual diversity in data science. Data Science, 1 (1-2). pp. 85-94. ISSN 2451-8484
Abstract
Data science is a young and rapidly expanding field, but one which has already experienced several waves of temporarily-ubiquitous methodological fashions. In this paper we argue that a diversity of ideas and methodologies is crucial for the long term success of the data science community. Towards the goal of a healthy, diverse ecosystem of different statistical models and approaches, we review how ideas spread in the scientific community and the role of incentives in influencing which research ideas scientists pursue. We conclude with suggestions for how universities, research funders and other actors in the data science community can help to maintain a rich, eclectic statistical environment.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 – IOS Press and the authors. This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution License (CC BY 4.0). |
Keywords: | Collective intelligence, diversity, contagion networks |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 May 2017 08:21 |
Last Modified: | 31 Jul 2018 21:17 |
Status: | Published |
Publisher: | IOS Press |
Identification Number: | 10.3233/DS-170003 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:115789 |