This session explores how Knowledge Meshes, Natural Language Processing (NLP) techniques, and the interplay between them help revolutionize how diverse stakeholders discover and operationalize planetary-scale data. By leveraging open web standards and cloud-native architectures, we can move beyond static repositories toward process-threaded systems that support real-time, multi-modal inquiries (e.g., “what if” scenarios) and provide a platform for next generation world models.

We invite presentations focusing on:

• Language-Driven Discovery: Using NLP and user "personas" to bridge the gap between complex datasets and diverse users, from scientists to policy makers.

• Operational Interoperability: Integrating FAIR and TRUST principles into low-latency, event-driven pipelines for faster product generation.

• Knowledge Integration: Federated methodologies that ensure factual grounding, reduce uncertainty, and align with international digital twin capabilities.

Through modular interfaces and AI/ML integration, this session aims to define a reference architecture for resilient, interoperable informatics that address critical socio-economic and ecological challenges across all Earth domains.

• EP - Earth and Planetary Surface Processes
• GC - Global Environmental Change
• OS - Ocean Sciences
• P - Planetary Sciences