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来源类型 | Report |
规范类型 | 报告 |
DOI | https://doi.org/10.7249/PEA150-1 |
来源ID | PE-A150-1 |
Decoding Data Science: The U.S. Coast Guard's Evolving Needs and Their Implications | |
Aaron C. Davenport; Michelle D. Ziegler; Abbie Tingstad; Katherine Anania; Daniel Ish; Nidhi Kalra; Scott Savitz; Rachel Liang; Melissa Bauman | |
发表日期 | 2020-06-24 |
出版年 | 2020 |
页码 | 24 |
语种 | 英语 |
摘要 | Like many large organizations, the U.S. Coast Guard has vast amounts of data that it could use to identify, predict, and solve pressing challenges. Data science could be valuable to the Coast Guard in a variety of domains, such as forecasting the resources needed for future trends in search-and-rescue missions, further automating aids to navigation, or automating fishery observations. In personnel areas, data science could help improve billet assignments, determine where to focus recruiting efforts, and boost employee retention. ,The Coast Guard has an opportunity to plot the path to determine service-specific uses, identify the strategy and driving mechanisms, and begin laying out a plan for the use of data science, which includes data collection, analysis, and management; artificial intelligence; and machine learning. This Perspective outlines the role that data science can play in decisionmaking processes and provides a selected set of key questions and sensitivities for the Coast Guard to consider in developing its future usage of data science. |
主题 | Data Science ; United States Coast Guard |
URL | https://www.rand.org/pubs/perspectives/PEA150-1.html |
来源智库 | RAND Corporation (United States) |
引用统计 | |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/524970 |
推荐引用方式 GB/T 7714 | Aaron C. Davenport,Michelle D. Ziegler,Abbie Tingstad,et al. Decoding Data Science: The U.S. Coast Guard's Evolving Needs and Their Implications. 2020. |
条目包含的文件 | ||||||
文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
RAND_PEA150-1.pdf(501KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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