Environmental Data Science (cambridge.org/eds) is a new, peer-reviewed, open access journal that is dedicated to the potential of artificial intelligence (AI) and data science to improve our understanding of the environment, including climate change. Published by Cambridge University Press, the journal covers the use of data-driven approaches (including AI, machine learning, data mining, computer vision, econometrics, statistics and data science) for:

• Biosphere (including ecology, hydrology, oceanography, glaciology, soil science);
• Climate change and its societal impacts (including forecasting, mitigation, and adaptation);
• Environmental policy and economics;
• Sustainability (including renewable energy, resource management, land use, agriculture and food);
• Water cycle, the atmospheric sciences and air quality (including climatology, meteorology, atmospheric chemistry / physics, paleoclimatology)

As of January 2021, we are open for submissions. We encourage authors to submit papers to be considered for publication in our first Volume.

Why submit to Environmental Data Science?

Here are five reasons why you might want to submit to EDS, elaborated in more detail in the sections below:

1. 1. Gain quality peer review feedback on your work from editors and reviewers who have expertise in the use of data science for the environment.
2. 2. Publish, if accepted, your work under open licensing to make it freely available to read, distribute and re-use in a venue that also provides you with options for making pre-prints, data and code openly available.
3. 3. Reach a wider audience through impact statements published with articles, conveying the significance of your work.
4. 4. Make EDS a formal publishing venue for your conference or workshop by proposing that we publish the outputs as a Special Collection.
5. 5. Help us build a community of authors, reviewers and editors advocating for the transformative potential of data science for a better understanding of the environment.

What kind of articles does EDS publish?

Full details of the scope of the journal can be found on our Instructions for Authors. We are interested in receiving:

• Application papers that research progress, or tackling a real-world problem, in an environmental field, enabled by data science.
• Methods papers: Novel data science methodology demonstrated in one or more environmental applications.
• Review articles (or Surveys) providing an overview of a subfield of Environmental Data Science.
• Position papers that explore issues related to the use of environmental data, including ethical, legal and policy issues, as well as data standards, protocols and services.
• Data papers that describe in a structured way, with a short narrative and accompanying metadata, important and re-usable environmental data sets that reside in publicly accessible repositories.
• Perspectives that provide an authoritative, personal view on the uptake or obstacles to AI and data science approaches for environmental problems.

Special Collections: workshops, conferences and events

We are keen to align with conferences, workshops and other events that are looking for a formal publishing venue for their outputs. If you run an event exploring the potential of AI and data science for the environment, send us a proposal for a special 'issue' (or collection). For more details, see the proposal guidelines for Special Collections.

Who is involved?

Claire Monteleoni (University of Colorado Boulder), who co-founded the Climate Informatics workshop, is the EDS Editor-in-Chief. See our Editorial Board for our full list of Editors and Advisory Board members.

How do I submit?

See our Instructions for Authors for full details of how to submit, which include a LaTeX template. Papers should be submitted through the EDS ScholarOne system.

What is the deadline?

EDS publishes on a continuous basis, rather than in issues, so there is no specific deadline. However, in order to stand a chance of a 2021 publication date, we encourage authors to submit by the end of April 2021.