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        <title>2025 FOSS4G NA | Bringing it all Together - Adeel Hassan</title>
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        <description>In this session from FOSS4G NA 2025, Adeel Hassan, a senior machine learning engineer at 84.2, presents Bringing it all Together: Knowledge Graphs, LLMs, and Cloud-Native Geospatial Data. Adeel discusses the Noah Knowledge Mesh project, an ambitious initiative funded by NOAA to bridge the gap between complex satellite datasets and real-world user questions through natural language processing. The presentation details a sophisticated architecture that combines Knowledge Graphs for data discovery with Large Language Models (LLMs) for data analysis. By translating natural language queries into a structured, custom formal language, the system can autonomously navigate thousands of NetCDF files, perform complex spatial-temporal computations using Xarray and Dask, and deliver high-level insights directly to the user. Highlights: 🛰️ The Missing Link: How AI and LLMs are finally connecting massive data silos with natural language user needs 🔄 Knowledge Graphs and Ontologies: Leveraging RDF and schema-based metadata to make NOAA's vast data catalogs discoverable 🧩 Virtual Zarr and Kerchunk: Transforming decades of legacy NetCDF files into high-performance, cloud-native virtual stores ⚙️ Structured Reasoning: Why 84.2 uses a custom formal language and Pydantic models instead of raw Python code generation for AI safety 🌐 Data Analysis Agents: A look at the multi-agent system that delegates tasks between data search, analysis, and user orchestration 🏢 Performance Optimization: Achieving a 40x speedup by storing Zarr metadata in Parquet format to handle massive time-series data 🏗️ Real-World Demos: Watch the system calculate sea surface temperature anomalies and compare temperatures across geographical regions in real-time For more content like this check out www.projectgeospatial.com #Geospatial #FOSS4G #LLM #KnowledgeGraph #NOAA #AI #CloudNative #Xarray #Dask #NetCDF #Zarr #DataScience #MachineLearning #ProjectGeospatial #DataDiscovery</description>
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