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totogo/awesome-knowledge-graph

  • What it is — A curated directory of knowledge-graph learning materials, databases, tools, datasets, services, events, and books. Its main organization separates infrastructure, knowledge engineering, datasets, and learning resources; it is a resource list rather than an ontology specification or tutorial.

  • Key concepts —

    • The infrastructure landscape is divided into graph databases, triple stores, graph-computing frameworks, visualization, graph construction, query languages, and managed hosting.
    • The listed Semantic Web and Linked Data stack includes RDF parsing and storage, triples/quads, inferencing, SPARQL endpoints, and W3C-compliant semantic graph databases.
    • Knowledge-graph construction can be mapping-driven: Morph-KGC uses RML mappings, while Ontop exposes SQL sources as a virtual knowledge graph through R2RML mappings.
    • Knowledge engineering includes web knowledge harvesting, seed-entity subgraph extraction, fuzzy deduplication/entity resolution, and link discovery.
    • Dataset examples distinguish general graphs, semantic networks, academic graphs, and domain graphs; their descriptions emphasize entities, facts, concepts, named entities, semantic relations, and the integration of heterogeneous sources.

  • How you’d use it — Use the categorized links to shortlist graph storage and computation systems, choose among Cypher, Gremlin, SPARQL, GraphQL+-, and GQL, find RDF libraries or graph visualization tools, and locate public knowledge-graph datasets. For construction, follow the listed RML/R2RML tools; for learning, start with the linked official Cypher/Gremlin documentation and community books or guides.

  • LLM angle — The listed Knowledge Graphs and LLMs in Action covers introducing knowledge graphs built from structured and unstructured sources into LLM applications and RAG pipelines. The Termboard entry also says its graphical term-and-relation editor can use ChatGPT, Google Bard, or another chatbot.

  • Pitfalls & lessons — The catalog explicitly marks Apache Marmotta as a retired Apache project, and Tencent Knowledge Graph as a beta service available only in Chinese. Its contribution guide also warns that maintainers may request changes to an existing pull request before merging it.

  • Verdict — A broad discovery index for knowledge-graph infrastructure, datasets, and learning links, but not a documented method for designing ontologies.

Sources consulted

  • readme.md
  • contributing.md