Fragile Earth 2024

Background Info

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 we also focus on two other aspects ,Generative and Foundational Models for Sustainable Development. The generative and foundational models in the context of climate change and sustainable development present significant potential and intricate challenges. Generative models, simulating advanced climate scenarios, offer a powerful tool for predicting local and global climate patterns, while foundational models, rooted in extensive knowledge bases, provide a solid understanding of climate systems. Together, they can also support the realization of digital twins for local contexts, aiding in sustainable development strategies. These models facilitate nuanced analyses of environmental impacts, enhance public awareness, and inform policymakers for sustainable practices. However, leveraging and integrating these models in a secure and trustworthy way presents significant challenges, including ensuring prediction accuracy, quantifying uncertainties, addressing biases in historical data, and navigating ethical concerns. Diverse datasets and knowledge integration are crucial to avoid disparities and bias, while ethical considerations are necessary to prevent dissemination of misinformation. Ironically, the high computational requirement for meeting all the desiderata for such large scale generative and foundation models also need to be addressed for their sustainable operationalization. Balancing the strengths of these models with their cons and costs is imperative for advancing the Sustainable Development Plan, fostering global awareness, and formulating effective policies for a resilient future. . 

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 resilience across a broad range of natural disasters such as wildfires, storms, and hurricanes.

List of Topics

• The Workshop will target both methodological and applied research agenda within these areas of investigation.

  
  
  • 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.
  • Any other topics related to the themes of the workshop are welcome!