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Название: Data Science and Human-Environment Systems
Автор: Steven M. Manson
Издательство: Cambridge University Press
Год: 2023
Страниц: 279
Язык: английский
Формат: pdf
Размер: 10.0 MB
Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data Science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings when it comes to human-environment research. There are challenges with social and environmental data, the methods that manipulate and analyze the information, and the theory underlying the data science itself; as well as significant legal, ethical and policy concerns. This timely book offers a comprehensive, balanced, and accessible account of the promise and problems of this work in terms of data, methods, theory, and policy. It demonstrates the need for data scientists to work with human-environment scholars to tackle pressing real-world problems, making it ideal for researchers and graduate students in Earth and environmental science, data science and the environmental social sciences. Data Science and cognate fields like Big Data and Artificial Intelligence hold great promise for studying human-environment systems.
Автор: Steven M. Manson
Издательство: Cambridge University Press
Год: 2023
Страниц: 279
Язык: английский
Формат: pdf
Размер: 10.0 MB
Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data Science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings when it comes to human-environment research. There are challenges with social and environmental data, the methods that manipulate and analyze the information, and the theory underlying the data science itself; as well as significant legal, ethical and policy concerns. This timely book offers a comprehensive, balanced, and accessible account of the promise and problems of this work in terms of data, methods, theory, and policy. It demonstrates the need for data scientists to work with human-environment scholars to tackle pressing real-world problems, making it ideal for researchers and graduate students in Earth and environmental science, data science and the environmental social sciences. Data Science and cognate fields like Big Data and Artificial Intelligence hold great promise for studying human-environment systems.