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- DS-170003 type PositionPaper assertion.
- author-list _1 0000-0003-0701-1274 assertion.
- author-list__1 _2 0000-0003-4517-2765 assertion.
- DS-170003 isPartOf 2451-8492 assertion.
- DS-170003 title "Maintaining intellectual diversity in data science" assertion.
- 2451-8492 title "Data Science" assertion.
- 024mrxd33 name "Department of Statistics, School of Mathematics, University of Leeds, UK" assertion.
- 05a28rw58 name "Computational Social Science, ETH Zurich, Zurich, Switzerland" assertion.
- 0000-0003-0701-1274 name "Richard P. Mann" assertion.
- 0000-0003-4517-2765 name "Olivia Woolley-Meza" assertion.
- DS-170003 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." assertion.
- DS-170003 date "2017-10-17" assertion.
- 0000-0003-0701-1274 email "r.p.mann@leeds.ac.uk" assertion.
- DS-170003 volume "1" assertion.
- 0000-0003-0701-1274 affiliation 024mrxd33 assertion.
- 0000-0003-4517-2765 affiliation 05a28rw58 assertion.
- DS-170003 issue "1-2" assertion.