Environmental Data Science (cambridge.org/eds) - the peer-reviewed, open-access journal at Cambridge University Press dedicated to the interface between data science and the environmental sciences - is pleased to continue its partnership with the Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice taking place at ACM's KDD 2024 Conference (August 26, Barcelona, Spain).
The workshop is a recurring event. Interested parties should see the AI4Good Foundation website for more information about its history and future events.
EDS invited authors accepted into the workshop to submit their work to a dedicated, curated special collection on Climate Mitigration, Adaptation and Environmental Justice. We also extend this invitation to authors who did not take part in the workshop but who are interested in these themes.
Since 2016, the Fragile Earth Workshop has brought together the research community to find and explore how data science can measure and progress climate and social issues, following the framework of the United Nations Sustainable Development Goals (SDGs). Over the years, Fragile Earth workshop has focused on SDGs. This year it is also focuses on Environmental Justice, which in the scope of scientific research can be defined as the effort to “document and redress the disproportionate environmental burdens and benefits associated with social inequalities” (Chakraborty et. al 2016), as well as SDG 13: Climate Action.
In 2021, the Intergovernmental Panel on Climate Change (IPCC) released their report on “physical science basis” stating that climate change was caused “unequivocally” by human action, while in 2022, they followed that up with their latest report on “impacts, adaptation and vulnerability” emphasizing that the time for action is now. These reports, parts of the Sixth Assessment Report (AR6), provide new estimates of the chances of crossing global warming thresholds, discuss the urgent need for adaptation pathways, and find that unless there are immediate, rapid, and large-scale reductions in greenhouse gas emissions, limiting warming will be beyond reach. The ramifications of these climate scenarios are devastating for the planet. As we fail to reach mitigation and adaptation targets, we will witness the triggering of more frequent sweltering heat waves, stronger storms, higher floods, severe droughts, and drastic ecosystem shifts, with disastrous consequences for human lives, economies and health, as well as biodiversity.
The application problems and agenda of interest include the Sustainable Development Goals, accelerating progress on the United Nations’ 2030 agenda, envisioning solutions for climate mitigation and adaptation, and measuring and diminishing the inequitable benefits and burdens across socioeconomic groups. In particular, the workshop has maintained a strong focus and community in the following areas: food security, sustainable agricultural practices and supply chains, ecosystem restoration, water management, sustainable energy, climate action and adaptation, socioeconomic equality, and disaster resilience. In the Fragile Earth Workshop, ML and AI researchers, social and behavioral scientists, as well as natural scientists and engineers, are invited to convene and discuss interdisciplinary solutions for progress towards the SDGs, Environmental Justice, and climate change mitigation and adaptation.
The methodological topics of interest are relevant areas of KDD, including but not limited to:
- generative and foundational models in the context of climate change and sustainable development
- diverse datasets and knowledge integration
- secure and trustworthy generative and foundational models
- the integration of physics into data-driven modeling and the use of machine learning, generative and foundational models to enhance physical simulations
- model explainability, uncertainty quantification, privacy and fairness questions in environmental modeling
- integration of symbolic and neural machine learning for accurate and interpretable machine learning, generative and foundational models
- causal learning in complex physical world as foundations for model trustworthiness
- sustainable computing paradigms for generative and foundation models
- ML applications at low-energy edge devices
- frameworks for helping the scientific and KDD communities to work together
- combining predictive and prescriptive tasks
- multi-agent systems for participatory modeling that integrate stakeholders into knowledge creation and decision processes geometric and topological deep learning for environmental modeling and assessment of environmental justice
Domains of interest include but are not limited to:
- food security, sustainable agricultural practices and supply chains, ecosystem restoration, water management, sustainable energy, climate action and adaptation, socioeconomic equality, and disaster resilience
- wildfire analytics: detection, prediction, and discovery; wildfire smoke and environmental fairness
- innovations in data science and predictive modeling, applied to earth sciences
- investigations centering sustainability, including but not limited to environmental justice
- data-informed climate change and resource management policy discussions
- carbon removal technologies
- easily usable and publicly available data+model+frameworks (possibly challenge problems) based on satellite/drone data to monitor and predictively model the fragile earth
- natural catastrophes under a changing climate ranging from improved modeling to development of resilient infrastructures
- economic/quantitative characterization of climate change risk and associated incentives towards policy/decision making.
Articles will be published as soon as possible after acceptance, in the interest of allowing authors to disseminate their work without unnecessary delay, and added to a curated page for the collection of articles.
Key dates are below but see the AI4Good website for details pertaining to the Fragile Earth 2024 workshop
- Paper Submission to Workshop: June 11th, 2024
- Paper Notification Date: June 28th, 2024
- Workshop Takes Place: August 26th, 2024
- Submission to EDS: November 29th, 2024
Please note the following key details, with more information available in the EDS Instructions for Authors:
Article Types: We assume full papers accepted into the workshop will either be submitted to EDS as application or methods papers, with authors of position papers and policy notes for the workshop invited to submit either position papers or perspectives. A full list of article types is here.
Templates: EDS LaTeX, Overleaf and Word templates are available but authors are not required to use these. Authors using the ACM template will need to adapt the article to include:
- Impact Statement: 120 words beneath the abstract describing the significance of the findings in language that can be understood by a wide audience
- Author contributions (using the CRedIT taxonomy as a guide)
- Competing interest statement
- Data availability statement
- Funding statement
See the EDS Instructions for Authors for more details about these statements. Note that we strongly encourage authors to make replication code and data available via open repositories, which should be linked to in the Data Availability Statement. Authors doing so will be awarded Open Data and Open Materials badges on publication.
- Yuzhou Chen (Temple University, USA)