Graphing Meaning Across Landscapes: Adapting USGS Grammar to Graph for Regional Decision Support
Enhance decision-making by making USGS science accessible and queryable.
The United States Geological Survey (USGS) produces scientific knowledge that supports critical environmental decisions, but much of this information remains locked in static glossaries and disconnected metadata. Without machine-readable vocabularies, discovering and integrating data across programs is difficult. This project tests whether an automated method called Grammar-to-Graph can parse complex definitions and map relationships between terms in a structured, machine-readable way — like a smart index that helps computers understand not just what a word means, but how it connects to other concepts. The project will deliver a proof-of-concept vocabulary, a replication guide adaptable by any USGS program, and clear guidelines for when automation is sufficient and when expert review is needed. This approach supports semantics-based data integration, a key step toward making USGS scientific information more discoverable and interoperable for federal partners and restoration practitioners.
Enhance decision-making by making USGS science accessible and queryable.
The United States Geological Survey (USGS) produces scientific knowledge that supports critical environmental decisions, but much of this information remains locked in static glossaries and disconnected metadata. Without machine-readable vocabularies, discovering and integrating data across programs is difficult. This project tests whether an automated method called Grammar-to-Graph can parse complex definitions and map relationships between terms in a structured, machine-readable way — like a smart index that helps computers understand not just what a word means, but how it connects to other concepts. The project will deliver a proof-of-concept vocabulary, a replication guide adaptable by any USGS program, and clear guidelines for when automation is sufficient and when expert review is needed. This approach supports semantics-based data integration, a key step toward making USGS scientific information more discoverable and interoperable for federal partners and restoration practitioners.