The document discusses linked data, ontologies, and inference. It provides examples of using RDFS and OWL to infer new facts from schemas and ontologies. Key points include:
- Linked Data uses URIs and HTTP to identify things and provide useful information about them via standards like RDF and SPARQL.
- Projects like LOD aim to develop best practices for publishing interlinked open datasets. FactForge and LinkedLifeData are examples that contain billions of statements across life science and general knowledge datasets.
- RDFS and OWL allow defining schemas and ontologies that enable inferring new facts through reasoning. Rules like rdfs:domain and rdfs:range allow inferring type information
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