Environmental Data Science
@EnvDataScience
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Environmental Data Science is an #OpenAccess @CambridgeUP journal dedicated to the use of data science & AI to enhance our understanding of the environment.
Cambridge, UK
Joined September 2020
📢 New CFP: Special Collection in EDS! 🌎. Calling for work exploring the convergence between #data-driven methodologies (#AI, #machinelearning) and physical modeling, building upon an upcoming workshop #EGU25. ℹ️ How to submit: 📅 Deadline: 31 Oct 2025
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New article!. Uncertainty bounds for long-term causal effects of perturbations in spatiotemporal systems. 👉 By @KDebeire, Andreas Gerhardus, Renée Bichler, @runge_jakob & Veronika Eyring. #spatiotemporalmodels #uncertaintyestimations
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Introducing our new Editor @PMoutis! Welcome to our board!. We have assembled an international advisory board of experts in the field of environmental data science. View our board here: #environment #data #climatechange
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New article!. Classification-informed estimation: the role of water-type clustering to improve neural network generalization for salinity and temperature estimation in coastal waters. 👉 By authors from @EdinburghUni, @CefasGovUK, @StirUni & @NOCnews
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ℹ️ Environmental Data Science is a peer-reviewed #OpenAccess journal published by @CambridgeUP. Give us a follow to find out more!.
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At #EnvironmentalDataScience, we are committed to forming close relationships with workshops and conferences to publish data-driven research for the environment. So far, we have worked with collaborators like #ClimateInformatics and #FragileEarth.
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Are you running a workshop on data science for the environment? Want your outputs to be reviewed for publication in a leading, thoughtful journal?. We would be thrilled to partner with you. To learn more and to partner with us, head to our website here 🔗
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New article!. Toward HydroLLM: a benchmark dataset for hydrology-specific knowledge assessment for large language models. 👉 By Dilara Kizilkaya, Ramteja Sajja, Yusuf Sermet and Ibrahim Demir . @IIHRUIowa @Tulane #LLM #AI #LargeLanguageModels #hydrology
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New article!. Discovering effective policies for land-use planning with neuroevolution. 👉 By Daniel Young, Olivier Francon, Elliot Meyerson, Clemens Schwingshackl, @JacobBieker, Hugo Cunha,.@babakatwork & Risto Miikkulainen. @OpenClimateFix @Cognizant
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New article!. The influence of correlated features on neural network attribution methods in geoscience. 👉 By @krell_evan, @AntoniosMamala2, Scott A. King, Philippe Tissot and @Iebertu . #artificialintelligence #AI #neuralnetworks
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📢 CALL FOR PAPERS: Connecting Data-Driven and Physical Approaches: Application to Climate Modeling and Earth System Observation. This special collection will build upon a workshop at #EGU25. Find out more: @brajard #climate #AI #forecasting
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New article!. Learning complex spatial dynamics of wildlife diseases with machine learning-guided partial differential equations. 👉 By authors from @UofSC, @USFWS, @umontana & @UWMadison . #spatialdynamics #ecology #ecologicaldiffusion #MachineLearning
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‼️ Want to learn more and to partner with us? Head to our webpage or contact us via email at: eds@cambridge.org 📩.
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And finally. 5️⃣ EDS can enhance the impact of your conference by curating your conference outputs into a dedicated special collection page. We also use #Altmetric to track the impact of your articles. 🌐.
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4️⃣ We are committed to #OpenResearch and adopt an open peer review model, awarding Open Practice Badges when an author makes the data and code underlying their articles openly available. 🔓.
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3️⃣ We are proud to operate an equitable fully #OpenAccess journal. Any author can publish on an OA basis, irrespective of their funding situation or affiliation. 💻.
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2️⃣ EDS gives you high-quality feedback from its expert editorial board. We can offer two flexible peer review models: an integration with the conference's existing process or peer review organised through EDS 📝.
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1️⃣ EDS is a dedicated venue for the use of data-driven methods for the environment. It provides researchers with a dedicated space to publish at the interface of both #datascience and #environmentalscience 🌍.
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✨ Running a workshop on data science (including #AI and #MachineLearning) for the environment? Partner with EDS! ✨ . EDS is a fully #OpenAccess journal published by @CambridgeUP . Here are 5 reasons why you should partner with us - a thread 🧵👇
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New article!. Investigating reduced-dimensional variability in aircraft-observed aerosol–cloud parameters. 👉 By authors from @USC, @uarizona & @NASA_Langley . #MachineLearning #aerosol #clouds #AtmosphericComposition
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Recently published!. Reflective error: a metric for assessing predictive performance at extreme events. 👉 By Robert Edwin Rouse (@Cambridge_Eng), @Henrymossmoss, Scott Hosking (@turinginst) , @AllanMcRobie and @emilyshuckburgh . #MachineLearning
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