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  # Rivers Knowledge Graph with Formal Ontology and Constraints
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  This repository contains a complete RDF knowledge graph with 118,047 triples representing structured knowledge about U.S. rivers, accompanied by a formal domain ontology and SHACL constraint definitions for validation. The knowledge graph is built from the rivers knowledge base and structured using a custom ontology (`worldmind_core.ttl`) defining six core classes (River, GeographicFeature, State, County, Country, RiverSystem) and 20+ properties for hydrological metrics, geographic relationships, and administrative hierarchies. SHACL shapes (`worldmind_constraints.shacl.ttl`) encode domain knowledge as machine-executable validation rules, including elevation constraints (source must exceed mouth), positive value requirements for measurements, geographic consistency checks, and tributary type validation. This knowledge graph implements the "licensing oracle" architecture where the graph functions as a mandatory validation gate for factual claims rather than merely a retrieval source. The formal ontology and constraints enable deterministic abstention, claim verification against logical rules, and domain-transferable validation mechanisms for truth-constrained LLM generation.
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  author={Ackermann, Richard and Emanuilov, Simeon},
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  year={2025}
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  }
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- ```
 
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+ ---
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+ license: cc-by-4.0
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+ language:
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+ - en
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+ ---
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  # Rivers Knowledge Graph with Formal Ontology and Constraints
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  This repository contains a complete RDF knowledge graph with 118,047 triples representing structured knowledge about U.S. rivers, accompanied by a formal domain ontology and SHACL constraint definitions for validation. The knowledge graph is built from the rivers knowledge base and structured using a custom ontology (`worldmind_core.ttl`) defining six core classes (River, GeographicFeature, State, County, Country, RiverSystem) and 20+ properties for hydrological metrics, geographic relationships, and administrative hierarchies. SHACL shapes (`worldmind_constraints.shacl.ttl`) encode domain knowledge as machine-executable validation rules, including elevation constraints (source must exceed mouth), positive value requirements for measurements, geographic consistency checks, and tributary type validation. This knowledge graph implements the "licensing oracle" architecture where the graph functions as a mandatory validation gate for factual claims rather than merely a retrieval source. The formal ontology and constraints enable deterministic abstention, claim verification against logical rules, and domain-transferable validation mechanisms for truth-constrained LLM generation.
 
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  author={Ackermann, Richard and Emanuilov, Simeon},
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  year={2025}
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  }
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+ ```