Making climate and disparate data more accessible with natural language processing (NLP) technology

Federal, State, local, Tribal, and territory leaders, policymakers, businesses, and their communities have a greater need than ever to access accurate and authoritative weather and climate data for allocating funding effectively, formulating policies, and implementing effective risk mitigation and resilience plans that safeguard a community's humanitarian, economic, and environmental well-being. Recent Artificial Intelligence and Machine Learning technological advances are beginning to enable communities with the ability to search and connect the dots between social, environmental, economic, demographic, ecosystem impacts. Specifically, Natural Language Processing (NLP) and Large Language Models (LLMs) present new opportunities to make this data more searchable, accessible, and usable for a variety of user personas to apply weather and climate data to their everyday lives. In this session, we explore NLP use cases, solution concepts, and related technology to help policy-makers better access and use weather and climate information for improved decision-making including:

• Exploring personas (e.g. Policy maker, Local Business owner, Chief Resilience Officer) and NLP sample use cases to optimize weather and climate product development, delivery, and messaging
• Principles and benefits of connecting disparate data with Data Mesh and Data Fabric architecture approaches: domain-oriented ownership, self-service, computational governance, data as a product
• Discussion of how Knowledge Graphs for NLP and LLMs can make complex weather and climate datasets more intuitive and searchable
• Coupling chatbot technology with user experience and interface (UX/UI) design principles to ease the burden of knowledge transfer to non-technical users
• Case Study: How Federal agencies deployed NLP technology for policy analysis with the GAMECHANGER tool and how the same approach can benefit future weather-water-climate enterprise policy