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Let's Make Gender Diversity in Data Science a Priority Right from the Start

The emergent field of data science is a critical driver for innovation in all sectors, a focus of tremendous workforce development, and an area of increasing importance within science, technology, engineering, and math (STEM). In all of its aspects, data science has the potential to narrow the gende...

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Detalles Bibliográficos
Autores principales: Berman, Francine D., Bourne, Philip E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4516301/
https://www.ncbi.nlm.nih.gov/pubmed/26213996
http://dx.doi.org/10.1371/journal.pbio.1002206
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author Berman, Francine D.
Bourne, Philip E.
author_facet Berman, Francine D.
Bourne, Philip E.
author_sort Berman, Francine D.
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description The emergent field of data science is a critical driver for innovation in all sectors, a focus of tremendous workforce development, and an area of increasing importance within science, technology, engineering, and math (STEM). In all of its aspects, data science has the potential to narrow the gender gap and set a new bar for inclusion. To evolve data science in a way that promotes gender diversity, we must address two challenges: (1) how to increase the number of women acquiring skills and working in data science and (2) how to evolve organizations and professional cultures to better retain and advance women in data science. Everyone can contribute.
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spelling pubmed-45163012015-07-29 Let's Make Gender Diversity in Data Science a Priority Right from the Start Berman, Francine D. Bourne, Philip E. PLoS Biol Perspective The emergent field of data science is a critical driver for innovation in all sectors, a focus of tremendous workforce development, and an area of increasing importance within science, technology, engineering, and math (STEM). In all of its aspects, data science has the potential to narrow the gender gap and set a new bar for inclusion. To evolve data science in a way that promotes gender diversity, we must address two challenges: (1) how to increase the number of women acquiring skills and working in data science and (2) how to evolve organizations and professional cultures to better retain and advance women in data science. Everyone can contribute. Public Library of Science 2015-07-27 /pmc/articles/PMC4516301/ /pubmed/26213996 http://dx.doi.org/10.1371/journal.pbio.1002206 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Perspective
Berman, Francine D.
Bourne, Philip E.
Let's Make Gender Diversity in Data Science a Priority Right from the Start
title Let's Make Gender Diversity in Data Science a Priority Right from the Start
title_full Let's Make Gender Diversity in Data Science a Priority Right from the Start
title_fullStr Let's Make Gender Diversity in Data Science a Priority Right from the Start
title_full_unstemmed Let's Make Gender Diversity in Data Science a Priority Right from the Start
title_short Let's Make Gender Diversity in Data Science a Priority Right from the Start
title_sort let's make gender diversity in data science a priority right from the start
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4516301/
https://www.ncbi.nlm.nih.gov/pubmed/26213996
http://dx.doi.org/10.1371/journal.pbio.1002206
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