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Hack weeks as a model for data science education and collaboration
Across many scientific disciplines, methods for recording, storing, and analyzing data are rapidly increasing in complexity. Skillfully using data science tools that manage this complexity requires training in new programming languages and frameworks as well as immersion in new modes of interaction...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6130377/ https://www.ncbi.nlm.nih.gov/pubmed/30127025 http://dx.doi.org/10.1073/pnas.1717196115 |
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author | Huppenkothen, Daniela Arendt, Anthony Hogg, David W. Ram, Karthik VanderPlas, Jacob T. Rokem, Ariel |
author_facet | Huppenkothen, Daniela Arendt, Anthony Hogg, David W. Ram, Karthik VanderPlas, Jacob T. Rokem, Ariel |
author_sort | Huppenkothen, Daniela |
collection | PubMed |
description | Across many scientific disciplines, methods for recording, storing, and analyzing data are rapidly increasing in complexity. Skillfully using data science tools that manage this complexity requires training in new programming languages and frameworks as well as immersion in new modes of interaction that foster data sharing, collaborative software development, and exchange across disciplines. Learning these skills from traditional university curricula can be challenging because most courses are not designed to evolve on time scales that can keep pace with rapidly shifting data science methods. Here, we present the concept of a hack week as an effective model offering opportunities for networking and community building, education in state-of-the-art data science methods, and immersion in collaborative project work. We find that hack weeks are successful at cultivating collaboration and facilitating the exchange of knowledge. Participants self-report that these events help them in both their day-to-day research as well as their careers. Based on our results, we conclude that hack weeks present an effective, easy-to-implement, fairly low-cost tool to positively impact data analysis literacy in academic disciplines, foster collaboration, and cultivate best practices. |
format | Online Article Text |
id | pubmed-6130377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-61303772018-09-12 Hack weeks as a model for data science education and collaboration Huppenkothen, Daniela Arendt, Anthony Hogg, David W. Ram, Karthik VanderPlas, Jacob T. Rokem, Ariel Proc Natl Acad Sci U S A Physical Sciences Across many scientific disciplines, methods for recording, storing, and analyzing data are rapidly increasing in complexity. Skillfully using data science tools that manage this complexity requires training in new programming languages and frameworks as well as immersion in new modes of interaction that foster data sharing, collaborative software development, and exchange across disciplines. Learning these skills from traditional university curricula can be challenging because most courses are not designed to evolve on time scales that can keep pace with rapidly shifting data science methods. Here, we present the concept of a hack week as an effective model offering opportunities for networking and community building, education in state-of-the-art data science methods, and immersion in collaborative project work. We find that hack weeks are successful at cultivating collaboration and facilitating the exchange of knowledge. Participants self-report that these events help them in both their day-to-day research as well as their careers. Based on our results, we conclude that hack weeks present an effective, easy-to-implement, fairly low-cost tool to positively impact data analysis literacy in academic disciplines, foster collaboration, and cultivate best practices. National Academy of Sciences 2018-09-04 2018-08-20 /pmc/articles/PMC6130377/ /pubmed/30127025 http://dx.doi.org/10.1073/pnas.1717196115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Huppenkothen, Daniela Arendt, Anthony Hogg, David W. Ram, Karthik VanderPlas, Jacob T. Rokem, Ariel Hack weeks as a model for data science education and collaboration |
title | Hack weeks as a model for data science education and collaboration |
title_full | Hack weeks as a model for data science education and collaboration |
title_fullStr | Hack weeks as a model for data science education and collaboration |
title_full_unstemmed | Hack weeks as a model for data science education and collaboration |
title_short | Hack weeks as a model for data science education and collaboration |
title_sort | hack weeks as a model for data science education and collaboration |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6130377/ https://www.ncbi.nlm.nih.gov/pubmed/30127025 http://dx.doi.org/10.1073/pnas.1717196115 |
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