52°North Spatial Information Research GmbH

Searching for relevant data is a fundamental task in geospatial and research data infrastructures (SDI/RDI) that demands precise and accurate results. Traditional search systems, which rely primarily on metadata, have notable limitations. These include the need for specialized knowledge and the inability to comprehend the contextual meaning of user queries. As a result, non-expert users often struggle to efficiently find the most relevant datasets. Furthermore, traditional metadata-based searches typically rely on exact keyword matching, which fail to capture the full semantic intent behind a query.

To address these limitations, we will explore a novel approach to geospatial data search using a Large Language Model (LLM) based framework in this blog post.

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