气候变化领域集成服务门户(CCPortal): Hack weeks as a model for data science education and collaboration

CCPortal

DOI	10.1073/pnas.1717196115
	Hack weeks as a model for data science education and collaboration
	Huppenkothen D.; Arendt A.; Hogg D.W.; Ram K.; VanderPlas J.T.; Rokem A.
发表日期	2018
ISSN	0027-8424
起始页码	8872
结束页码	8877
卷号	115 期号:36
英文摘要	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. © 2018 National Academy of Sciences. All Rights Reserved.
英文关键词	Data science; Education; Interdisciplinary collaboration; Reproducibility
语种	英语
scopus关键词	adult; article; career; data analysis; education; female; human; human experiment; immersion; literacy; male; reproducibility; self report; educational model; information dissemination; interdisciplinary education; science; university; Humans; Information Dissemination; Interdisciplinary Studies; Models, Educational; Science; Universities
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160471
作者单位	Huppenkothen, D., Institute for Data-Intensive Research in Astrophysics and Cosmology, Department of Astronomy, University of Washington, Seattle, WA 98195, United States, Center for Data Science, New York University, New York, NY 10003, United States, Center for Cosmology and Particle Physics, Department of Physics, New York University, New York, NY 10003, United States, University of Washington eScience Institute, Washington Research Foundation Data Science Studio, University of Washington, Seattle, WA 98105, United States; Arendt, A., University of Washington eScience Institute, Washington Research Foundation Data Science Studio, University of Washington, Seattle, WA 98105, United States, Polar Science Center, Applied Physics Laboratory, University of Washington, Seattle, WA 98105-6698, United States; Hogg, D.W., Center for Data Science, New York University, New York, NY 10003, United States, Center for Cosmology and Particle Physics, Department of Physics, New York University, New York, NY 100...
推荐引用方式 GB/T 7714	Huppenkothen D.,Arendt A.,Hogg D.W.,et al. Hack weeks as a model for data science education and collaboration[J],2018,115(36).
APA	Huppenkothen D.,Arendt A.,Hogg D.W.,Ram K.,VanderPlas J.T.,&Rokem A..(2018).Hack weeks as a model for data science education and collaboration.Proceedings of the National Academy of Sciences of the United States of America,115(36).
MLA	Huppenkothen D.,et al."Hack weeks as a model for data science education and collaboration".Proceedings of the National Academy of Sciences of the United States of America 115.36(2018).