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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. https://doi.org/10.3233/DS-170003 http://purl.org/dc/terms/date 2017-10-17 https://doi.org/10.3233/DS-170003 http://purl.org/dc/terms/isPartOf http://id.crossref.org/issn/2451-8492 https://doi.org/10.3233/DS-170003 http://purl.org/dc/terms/title Maintaining intellectual diversity in data science https://doi.org/10.3233/DS-170003 http://purl.org/ontology/bibo/issue 1-2 https://doi.org/10.3233/DS-170003 http://purl.org/ontology/bibo/volume 1 https://doi.org/10.3233/DS-170003 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/PositionPaper https://orcid.org/0000-0003-0701-1274 http://schema.org/affiliation https://ror.org/024mrxd33 https://orcid.org/0000-0003-0701-1274 http://schema.org/email r.p.mann@leeds.ac.uk https://orcid.org/0000-0003-0701-1274 http://xmlns.com/foaf/0.1/name Richard P. 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