Cambridge University Press launches Environmental Data Science journal

Cambridge University Press is launching a new, Open Access journal –

Environmental Data Science

– dedicated to the potential of artificial intelligence and data science to enhance our understanding of the environment, and to address climate change.

It will promote interdisciplinary approaches that allow researchers to use insights from the world’s ever-growing store of environmental data to support analysis and inform decision-making.

The journal will be led by Editor-in-Chief Claire Monteleoni, Associate Professor in the Department of Computer Science, University of Colorado Boulder, one of the leading researchers in the interdisciplinary field of climate informatics. Claire will lead a diverse editorial board, with expertise in how data can be used for an array of environmental problems.

The journal will be open for submissions from December 10th 2020, and looks forward to publishing a wide range of articles using data-driven approaches to understand the biosphere; climate change and its societal impacts; environmental policy and economics; sustainability; water cycle, atmospheric science and air quality. All articles will be accompanied by an impact statement to summarise the significance of the findings for a wider audience.

Caroline Black, Publishing Director of STM Journals at Cambridge University Press said: “We’re delighted to be working with Professor Monteleoni, who is a leader in this area as evidenced by the Climate Informatics conference that she co-founded.

“This new title is part of a growing list of Cambridge publications exploring the impact of data science. We see this as a great opportunity for the Press to serve a new generation of researchers who are innovating with skills and techniques to analyse data. We also see potential for

Environmental Data Science

to engage with the broader open research movement that is transforming the way research is disseminated.”

Claire Monteleoni, Editor-in-Chief said: “Data science broadly defined — AI, machine learning, statistics, and data mining — is the key to unlock insights from environmental data, and help us address major challenges, including climate change.

Environmental Data Science

will highlight advances in addressing complex environmental problems using machine learning and data-driven approaches. I’m excited to be working with Cambridge University Press on this new open access journal.”

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Environmental Data Science

joins two recently launched journals,

Data & Policy

and

Data-Centric Engineering

, which share a similar focus on data science, open research and innovative formats. More information about the journal can be found on its webpage at

https:/

environmental-data-science