{ "schema": "ontology_agent_kb_pack/v1", "generated_at": "2026-06-25", "purpose": "Machine-readable entrypoint for agents that need precise recall over the ontology, AI, and Palantir research KB.", "workspace_root": "D:\\knowledge\\ontology", "local_preview_url": "http://127.0.0.1:8787/", "canonical_blog_url": "https://renxuai.com/ontology/", "metrics": { "source_count": 803, "core_sources": 150, "candidate_sources": 332, "low_priority_sources": 321, "selected_sources": 382, "chunks": 2157, "claims": 1307, "entities": 1804, "relations": 16721, "bucket_counts": { "palantir": 142, "academic": 489, "technical": 105, "books": 27, "commercial": 32, "synthesis": 8 }, "quality_counts": { "official_docs": 101, "peer_reviewed_survey": 51, "official_standard": 51, "primary_source": 41, "peer_reviewed_seminal": 7, "peer_reviewed": 136, "widely_cited": 53, "scholarly_book": 6, "secondary_source": 33, "preprint": 115, "scholarly_index": 167, "marketing": 36, "official_open_source": 1, "preprint_benchmark": 5 } }, "entrypoints": { "agent_guide": "research/AGENT_GUIDE.md", "triaged_sources": "research/sources/triaged_sources.jsonl", "core_sources": "research/sources/core_sources.jsonl", "candidate_sources": "research/sources/candidate_sources.jsonl", "chunks": "research/chunks/chunks.jsonl", "claims": "research/extractions/claims.jsonl", "entities": "research/graph/entities.jsonl", "relations": "research/graph/relations.jsonl", "graph_json": "research/graph/graph.json", "source_index": "research/indexes/source_index.json", "concept_index": "research/indexes/concept_index.json", "evidence_matrix": "research/synthesis/evidence_matrix.json", "source_routes": "research/synthesis/source_routes.md", "nature_submission_pack": "research/synthesis/nature_submission_pack.md", "completion_audit": "research/synthesis/completion_audit.md", "site_root": "site/index.html" }, "evidence_policy": { "cite_first": [ "core", "candidate" ], "academic_proof": [ "academic", "books", "technical" ], "architecture_evidence": [ "official_docs", "official_standard", "primary_source" ], "commercial_boundary": "Commercial and vendor material can support implementation patterns, architecture claims, adoption signals, and market context, but not independent academic proof.", "palantir_boundary": "Palantir official docs support how Palantir describes its architecture; they do not independently validate safety, ROI, fairness, or public legitimacy.", "frontier_boundary": "Phase 11 arXiv items are frontier direction unless later peer-reviewed; mark them as preprint evidence." }, "query_recipes": [ { "name": "Palantir ontology architecture", "command": "python scripts\\search_kb.py \"Palantir AIP ontology action type MCP evals observability\" --concept palantir_ontology --limit 8", "use_for": "Retrieve official Palantir architecture evidence about Ontology, AIP, OMCP, actions, permissions, evals, and observability." }, { "name": "Ontology foundations", "command": "python scripts\\search_kb.py \"explicit specification conceptualization formal ontology knowledge sharing\" --concept ontology --limit 8", "use_for": "Retrieve foundational ontology definitions and design principles." }, { "name": "Scientific ontology infrastructure", "command": "python scripts\\search_kb.py \"Gene Ontology OBO Foundry ROBOT ODK HPO Monarch DeepGO-SE\" --concept scientific_ontology_infrastructure --limit 10", "use_for": "Retrieve scientific ontology infrastructure evidence for Nature-style argumentation." }, { "name": "Ontology evaluation and lifecycle governance", "command": "python scripts\\search_kb.py \"OntoClean OOPS ontology evolution MIRO NeOn FAIRsharing\" --concept ontology_quality --limit 10", "use_for": "Retrieve Phase 16 sources about ontology conceptual quality, pitfall scanning, evolution, reporting, reuse, and lifecycle governance." }, { "name": "Semantic data infrastructure", "command": "python scripts\\search_kb.py \"LinkML SSSOM Croissant Wikidata OBDA FAIR Data Point virtual knowledge graph\" --concept semantic_schema --limit 10", "use_for": "Retrieve Phase 14 sources about typed schema, ontology mappings, ML dataset metadata, OBDA/VKG, and machine-actionable metadata." }, { "name": "Mappings and dataspaces", "command": "python scripts\\search_kb.py \"R2RML RML Morph-KGC International Data Spaces Gaia-X Dataspace Protocol\" --concept mapping_language --limit 10", "use_for": "Retrieve Phase 15 sources about data-to-RDF mappings, KG construction pipelines, and federated dataspace semantics." }, { "name": "Policy, privacy, and industrial semantics", "command": "python scripts\\search_kb.py \"SPARQL federated query DPV XACML Solid OPC UA SAREF eClass IEC CDD\" --concept industrial_semantic_standards --limit 10", "use_for": "Retrieve Phase 16 sources about federated query, privacy/access-control vocabularies, decentralized linked data, and industrial information models." }, { "name": "LLM + KG + RAG", "command": "python scripts\\search_kb.py \"LLM knowledge graph RAG GraphRAG ontology grounded retrieval\" --concept llm_kg --limit 10", "use_for": "Retrieve evidence about LLM/KG integration, RAG, GraphRAG, ontology-grounded RAG, and KGQA." }, { "name": "2026 frontier evidence", "command": "python scripts\\search_kb.py \"phase11\" --limit 10", "use_for": "Retrieve recent 2026 sources and preprints; use as frontier direction, not settled consensus." }, { "name": "Governance and sociotechnical critique", "command": "python scripts\\search_kb.py \"classification infrastructure public sector governance NHS FDP privacy accountability\" --concept ai_governance --limit 10", "use_for": "Retrieve governance, public-sector, privacy, accountability, and sociotechnical critique evidence." }, { "name": "Commercial material boundary", "command": "python scripts\\search_kb.py \"semantic layer data product enterprise AI context engine\" --limit 8", "use_for": "Retrieve commercial implementation comparators; do not use these as academic proof." } ], "priority_concepts": [ { "concept": "ontology", "chunk_count": 1154, "direct_source_count": 209, "top_sources": [ { "id": "phase2-pal-aip-observability-overview-2026", "title": "AIP observability: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-observability/overview", "retrieval_tags": [ "aip-observability", "core", "governance", "logs", "metrics", "palantir", "tracing", "workflow-lineage" ] }, { "id": "phase2-pal-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluate Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "core", "custom-evaluation", "governed-action", "ontology-edits", "palantir", "simulation", "validation", "write-capable-agents" ] }, { "id": "core-palantir-ontology-overview-2026", "title": "Ontology building: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology/overview", "retrieval_tags": [ "actions", "core", "digital-twin", "foundry", "kinetic-elements", "ontology", "operational-layer", "palantir", "semantic-elements" ] }, { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "w3c_shacl_2017", "title": "Shapes Constraint Language (SHACL)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2017, "url": "https://www.w3.org/TR/shacl", "retrieval_tags": [ "constraints", "core", "data-quality", "ontology-governance", "rdf", "semantic-governance", "semantic-web", "shacl", "validation", "w3c" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "oa-https-doi-org-10-1109-tnnls-2021-3070843", "title": "A Survey on Knowledge Graphs: Representation, Acquisition, and Applications", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://ieeexplore.ieee.org/document/9416312", "retrieval_tags": [ "applications", "core", "foundational", "kg-completion", "knowledge-acquisition", "knowledge-graph", "ontology_ai", "openalex", "representation-learning", "survey" ] }, { "id": "arxiv-2306-08302v3", "title": "Unifying Large Language Models and Knowledge Graphs: A Roadmap", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2306.08302", "retrieval_tags": [ "arxiv", "core", "grounding", "hybrid-ai", "knowledge-graph", "large-language-models", "llm", "llm-kg", "ontology_ai", "reasoning", "roadmap", "survey" ] } ] }, { "concept": "formal_ontology", "chunk_count": 26, "direct_source_count": 10, "top_sources": [ { "id": "w3c_shacl_2017", "title": "Shapes Constraint Language (SHACL)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2017, "url": "https://www.w3.org/TR/shacl", "retrieval_tags": [ "constraints", "core", "data-quality", "ontology-governance", "rdf", "semantic-governance", "semantic-web", "shacl", "validation", "w3c" ] }, { "id": "w3c_skos_reference_2009", "title": "SKOS Simple Knowledge Organization System Reference", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2009, "url": "https://www.w3.org/TR/skos-reference", "retrieval_tags": [ "controlled-vocabulary", "core", "retrieval", "semantic-web", "skos", "standard", "taxonomy", "w3c" ] }, { "id": "core-bfo-iso-21838-2", "title": "Information technology - Top-level ontologies - Part 2: Basic Formal Ontology (BFO)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2021, "url": "https://www.iso.org/standard/74572.html", "retrieval_tags": [ "bfo", "core", "interoperability", "iso-21838", "standard", "top-level-ontology", "upper-ontology" ] }, { "id": "core-w3c-owl2-overview", "title": "OWL 2 Web Ontology Language Document Overview", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2012, "url": "https://www.w3.org/TR/owl2-overview", "retrieval_tags": [ "core", "description-logic", "knowledge-representation", "ontology", "ontology-language", "owl", "reasoning", "semantic-web", "standard", "standards", "w3c" ] }, { "id": "core-guarino-1998-formal-ontology-information-systems", "title": "Formal Ontology in Information Systems", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 1998, "url": "https://dl.acm.org/doi/10.5555/521720.521722", "retrieval_tags": [ "conceptual-modeling", "core", "formal-ontology", "information-systems" ] }, { "id": "core-niles-pease-2001-sumo", "title": "Towards a Standard Upper Ontology", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2001, "url": "https://doi.org/10.1145/505168.505170", "retrieval_tags": [ "core", "formal-ontology", "interoperability", "standardization", "sumo", "upper-ontology" ] }, { "id": "oa-https-openalex-org-w2108234081", "title": "Ontological foundations for structural conceptual models", "bucket": "academic", "quality_signal": "scholarly_index", "triage_tier": "core", "year": 2005, "url": "https://research.utwente.nl/en/publications/ontological-foundations-for-structural-conceptual-models", "retrieval_tags": [ "commercial", "conceptual-modeling", "core", "model-quality", "ontouml", "openalex" ] }, { "id": "guarino_1998_fois", "title": "Formal Ontology and Information Systems", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1998, "url": "https://ontolog.cim3.net/file/resource/historic-archives/FOIS-community/Guarino98_Formal-Ontology-and-Information-Systems_FOIS-1998_NicolaGuarino_19980606to08.pdf", "retrieval_tags": [ "fois", "formal-ontology", "information-systems", "intended-meaning" ] } ] }, { "concept": "semantic_web", "chunk_count": 249, "direct_source_count": 52, "top_sources": [ { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "core-w3c-rdf-11-concepts", "title": "RDF 1.1 Concepts and Abstract Syntax", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2014, "url": "https://www.w3.org/TR/rdf11-concepts", "retrieval_tags": [ "core", "graph-data", "linked-data", "rdf", "semantic-web", "standard", "w3c" ] }, { "id": "w3c_shacl_2017", "title": "Shapes Constraint Language (SHACL)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2017, "url": "https://www.w3.org/TR/shacl", "retrieval_tags": [ "constraints", "core", "data-quality", "ontology-governance", "rdf", "semantic-governance", "semantic-web", "shacl", "validation", "w3c" ] }, { "id": "phase2-w3c-prov-o-2013", "title": "PROV-O: The PROV Ontology", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://www.w3.org/TR/prov-o", "retrieval_tags": [ "audit", "core", "lineage", "owl", "prov-o", "provenance", "trustworthy-ai", "w3c" ] }, { "id": "w3c_skos_reference_2009", "title": "SKOS Simple Knowledge Organization System Reference", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2009, "url": "https://www.w3.org/TR/skos-reference", "retrieval_tags": [ "controlled-vocabulary", "core", "retrieval", "semantic-web", "skos", "standard", "taxonomy", "w3c" ] }, { "id": "core-w3c-sparql-11-query", "title": "SPARQL 1.1 Query Language", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://www.w3.org/TR/sparql11-query", "retrieval_tags": [ "core", "graph-query", "knowledge-graph", "query", "query-language", "rdf", "semantic-web", "sparql", "standard", "standards", "w3c" ] }, { "id": "oa-https-doi-org-10-3233-sw-140134", "title": "DBpedia – A large-scale, multilingual knowledge base extracted from Wikipedia", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2015, "url": "https://doi.org/10.3233/SW-140134", "retrieval_tags": [ "commercial", "core", "dbpedia", "foundational", "knowledge-graph", "linked-data", "openalex" ] }, { "id": "core-berners-lee-2001-semantic-web", "title": "The Semantic Web", "bucket": "technical", "quality_signal": "widely_cited", "triage_tier": "core", "year": 2001, "url": "https://doi.org/10.1038/scientificamerican0501-34", "retrieval_tags": [ "agents", "core", "linked-data", "machine-readable-data", "metadata", "semantic-web" ] } ] }, { "concept": "knowledge_graph", "chunk_count": 189, "direct_source_count": 49, "top_sources": [ { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "oa-https-doi-org-10-1109-tnnls-2021-3070843", "title": "A Survey on Knowledge Graphs: Representation, Acquisition, and Applications", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://ieeexplore.ieee.org/document/9416312", "retrieval_tags": [ "applications", "core", "foundational", "kg-completion", "knowledge-acquisition", "knowledge-graph", "ontology_ai", "openalex", "representation-learning", "survey" ] }, { "id": "arxiv-2306-08302v3", "title": "Unifying Large Language Models and Knowledge Graphs: A Roadmap", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2306.08302", "retrieval_tags": [ "arxiv", "core", "grounding", "hybrid-ai", "knowledge-graph", "large-language-models", "llm", "llm-kg", "ontology_ai", "reasoning", "roadmap", "survey" ] }, { "id": "phase2-w3c-prov-o-2013", "title": "PROV-O: The PROV Ontology", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://www.w3.org/TR/prov-o", "retrieval_tags": [ "audit", "core", "lineage", "owl", "prov-o", "provenance", "trustworthy-ai", "w3c" ] }, { "id": "phase2-iso-iec-42001-2023", "title": "ISO/IEC 42001:2023 Artificial intelligence - Management system", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2023, "url": "https://www.iso.org/standard/81230.html", "retrieval_tags": [ "ai-management-system", "core", "governance", "iso", "lifecycle", "policy", "risk-management" ] }, { "id": "oa-https-doi-org-10-3233-sw-160218", "title": "Knowledge graph refinement: A survey of approaches and evaluation methods", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2016, "url": "https://doi.org/10.3233/SW-160218", "retrieval_tags": [ "core", "foundational", "knowledge-graph", "openalex", "quality", "refinement", "survey" ] }, { "id": "phase2-he-2024-g-retriever", "title": "G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2402.07630", "retrieval_tags": [ "core", "g-retriever", "graph-qa", "graph-rag", "hallucination", "knowledge-graph", "rag", "retrieval", "subgraph-retrieval", "textual-graphs" ] }, { "id": "ont-ai-023", "title": "HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2405.14831", "retrieval_tags": [ "agent-memory", "associative-memory", "core", "graph-retrieval", "hipporag", "knowledge-graph", "llm", "long-term-memory", "multi-hop", "multi-hop-qa", "neurips-2024", "pagerank" ] } ] }, { "concept": "scientific_ontology_infrastructure", "chunk_count": 69, "direct_source_count": 19, "top_sources": [ { "id": "core-gene-ontology-2000", "title": "Gene Ontology: Tool for the Unification of Biology", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 2000, "url": "https://doi.org/10.1038/75556", "retrieval_tags": [ "annotation", "biology", "biomedical-ontology", "controlled-vocabulary", "core", "data-integration", "gene-ontology", "scientific-infrastructure" ] }, { "id": "phase7-obo-foundry-2021-operationalizing-open-data-principles", "title": "OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2021, "url": "https://doi.org/10.1093/database/baab069", "retrieval_tags": [ "biomedical-ontology", "governance", "interoperability", "obo-foundry", "ontology-governance", "phase7", "scientific-infrastructure", "versioning" ] }, { "id": "phase7-gene-ontology-knowledgebase-2023", "title": "The Gene Ontology knowledgebase in 2023", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://doi.org/10.1093/genetics/iyad031", "retrieval_tags": [ "biology", "biomedical-ontology", "gene-ontology", "go-cam", "ontology-infrastructure", "phase7", "scientific-infrastructure", "validation" ] }, { "id": "phase7-edam-bioinformatics-ontology-2013", "title": "EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2013, "url": "https://doi.org/10.1093/bioinformatics/btt113", "retrieval_tags": [ "bioinformatics", "edam", "ontology-infrastructure", "phase7", "scientific-workflows", "tool-semantics", "workflow" ] }, { "id": "phase7-go-cam-causal-activity-modeling-2019", "title": "Gene Ontology Causal Activity Modeling (GO-CAM) moves beyond GO annotations to structured descriptions of biological functions and systems", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2019, "url": "https://doi.org/10.1038/s41588-019-0500-1", "retrieval_tags": [ "biology", "causal-modeling", "gene-ontology", "go-cam", "knowledge-graph", "ontology-infrastructure", "phase7", "scientific-infrastructure" ] }, { "id": "phase3-star-griesemer-1989-boundary-objects", "title": "Institutional Ecology, 'Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1989, "url": "https://doi.org/10.1177/030631289019003001", "retrieval_tags": [ "boundary-objects", "classification", "coordination", "infrastructure", "phase3", "sts" ] }, { "id": "phase14-hoyt-gyori-2024-o3-guidelines-curated-resources", "title": "The O3 guidelines: open data, open code, and open infrastructure for sustainable curated scientific resources", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://doi.org/10.1038/s41597-024-03406-w", "retrieval_tags": [ "community-curation", "knowledge-infrastructure", "o3-guidelines", "open-code", "open-data", "open-infrastructure", "phase14", "scientific-infrastructure" ] }, { "id": "oa-https-doi-org-10-1093-nar-gkaa1113", "title": "The Gene Ontology resource: enriching a GOld mine", "bucket": "academic", "quality_signal": "scholarly_index", "triage_tier": "candidate", "year": 2020, "url": "https://openalex.org/W3112600195", "retrieval_tags": [ "foundational", "openalex" ] } ] }, { "concept": "biomedical_ontology", "chunk_count": 79, "direct_source_count": 18, "top_sources": [ { "id": "core-gene-ontology-2000", "title": "Gene Ontology: Tool for the Unification of Biology", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 2000, "url": "https://doi.org/10.1038/75556", "retrieval_tags": [ "annotation", "biology", "biomedical-ontology", "controlled-vocabulary", "core", "data-integration", "gene-ontology", "scientific-infrastructure" ] }, { "id": "phase7-obo-foundry-2021-operationalizing-open-data-principles", "title": "OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2021, "url": "https://doi.org/10.1093/database/baab069", "retrieval_tags": [ "biomedical-ontology", "governance", "interoperability", "obo-foundry", "ontology-governance", "phase7", "scientific-infrastructure", "versioning" ] }, { "id": "phase7-ontology-development-kit-toolkit-2022", "title": "Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2022, "url": "https://doi.org/10.1093/database/baac087", "retrieval_tags": [ "biomedical-ontology", "maintenance", "obo", "ontology-development-kit", "ontology-engineering", "phase7", "reproducibility", "tooling" ] }, { "id": "phase11-ali-2026-ontology-grounded-kg-clinical-hallucinations", "title": "Ontology-grounded knowledge graphs for mitigating hallucinations in large language models for clinical question answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://doi.org/10.1016/j.jbi.2026.104993", "retrieval_tags": [ "biomedical-ontology", "clinical-qa", "hallucination-mitigation", "knowledge-graph", "llm", "ontology-grounded-rag", "phase11", "rag", "safety-critical-ai" ] }, { "id": "phase11-hamed-rocha-2026-biomedical-rag-majority-voting-verification-protocol", "title": "Protocol for evaluating ChatGPT in biomedical association generation and verification using a RAG-enabled, cross-model majority voting workflow", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://doi.org/10.1016/j.xpro.2026.104533", "retrieval_tags": [ "biomedical-ontology", "biomedical-verification", "cross-model-voting", "evaluation-protocol", "fact-checking", "hallucination-mitigation", "phase11", "rag", "validation" ] }, { "id": "phase7-robot-automating-ontology-workflows-2019", "title": "ROBOT: A Tool for Automating Ontology Workflows", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2019, "url": "https://doi.org/10.1186/s12859-019-3002-3", "retrieval_tags": [ "automation", "biomedical-ontology", "ci-cd", "ontology-engineering", "ontology-workflows", "phase7", "robot", "validation" ] }, { "id": "phase7-gene-ontology-knowledgebase-2023", "title": "The Gene Ontology knowledgebase in 2023", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://doi.org/10.1093/genetics/iyad031", "retrieval_tags": [ "biology", "biomedical-ontology", "gene-ontology", "go-cam", "ontology-infrastructure", "phase7", "scientific-infrastructure", "validation" ] }, { "id": "smith_etal_2007_obo_foundry", "title": "The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2007, "url": "https://doi.org/10.1038/nbt1346", "retrieval_tags": [ "biomedical-ontology", "governance", "interoperability", "obo-foundry", "versioning" ] } ] }, { "concept": "ontology_engineering", "chunk_count": 57, "direct_source_count": 19, "top_sources": [ { "id": "phase2-li-garijo-poveda-2025-llm-oe-review", "title": "Large Language Models for Ontology Engineering: A Systematic Literature Review", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2025, "url": "https://www.semantic-web-journal.net/content/large-language-models-ontology-engineering-systematic-literature-review", "retrieval_tags": [ "benchmarks", "core", "human-in-the-loop", "llm", "ontology-engineering", "ontology-governance", "survey", "systematic-review", "validation" ] }, { "id": "core-bfo-iso-21838-2", "title": "Information technology - Top-level ontologies - Part 2: Basic Formal Ontology (BFO)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2021, "url": "https://www.iso.org/standard/74572.html", "retrieval_tags": [ "bfo", "core", "interoperability", "iso-21838", "standard", "top-level-ontology", "upper-ontology" ] }, { "id": "core-uschold-gruninger-1996-principles-methods", "title": "Ontologies: Principles, Methods and Applications", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 1996, "url": "https://doi.org/10.1017/S0269888900007797", "retrieval_tags": [ "competency-questions", "core", "evaluation", "methodology", "ontology-engineering" ] }, { "id": "phase2-gangemi-2005-ontology-design-patterns", "title": "Ontology Design Patterns for Semantic Web Content", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2005, "url": "https://doi.org/10.1007/11574620_21", "retrieval_tags": [ "core", "ontology-design-patterns", "ontology-engineering", "reuse", "semantic-web", "validation" ] }, { "id": "core-staab-studer-2009-handbook-ontologies", "title": "Handbook on Ontologies", "bucket": "books", "quality_signal": "widely_cited", "triage_tier": "core", "year": 2009, "url": "https://doi.org/10.1007/978-3-540-92673-3", "retrieval_tags": [ "book", "core", "handbook", "mapping", "matching", "ontology-engineering", "ontology-learning", "reasoning", "semantic-web" ] }, { "id": "phase2-kommineni-2024-llm-ontology-kg-construction", "title": "From human experts to machines: An LLM supported approach to ontology and knowledge graph construction", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2403.08345", "retrieval_tags": [ "competency-questions", "core", "evaluation", "human-in-the-loop", "knowledge-graph-construction", "llm", "ontology-construction", "ontology-engineering" ] }, { "id": "core-noy-mcguinness-2001-ontology-101", "title": "Ontology Development 101: A Guide to Creating Your First Ontology", "bucket": "technical", "quality_signal": "widely_cited", "triage_tier": "core", "year": 2001, "url": "https://protege.stanford.edu/publications/ontology_development/ontology101.pdf", "retrieval_tags": [ "classes", "core", "ontology-development", "ontology-engineering", "properties", "protege", "slots", "tutorial" ] }, { "id": "phase7-ontology-development-kit-toolkit-2022", "title": "Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2022, "url": "https://doi.org/10.1093/database/baac087", "retrieval_tags": [ "biomedical-ontology", "maintenance", "obo", "ontology-development-kit", "ontology-engineering", "phase7", "reproducibility", "tooling" ] } ] }, { "concept": "ontology_generation", "chunk_count": 14, "direct_source_count": 5, "top_sources": [ { "id": "phase2-kommineni-2024-llm-ontology-kg-construction", "title": "From human experts to machines: An LLM supported approach to ontology and knowledge graph construction", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2403.08345", "retrieval_tags": [ "competency-questions", "core", "evaluation", "human-in-the-loop", "knowledge-graph-construction", "llm", "ontology-construction", "ontology-engineering" ] }, { "id": "phase2-rigor-2025-rag-ontologies-rdb", "title": "Retrieval-Augmented Generation of Ontologies from Relational Databases", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "core", "year": 2025, "url": "https://arxiv.org/abs/2506.01232", "retrieval_tags": [ "core", "ontology-generation", "owl", "rag", "relational-database", "rigor", "schema", "semantic-layer", "validation" ] }, { "id": "ont-ai-004", "title": "LLMs4OL: Large Language Models for Ontology Learning", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2307.16648", "retrieval_tags": [ "benchmark", "core", "iswc-2023", "llm", "llms4ol", "ontology-engineering", "ontology-learning", "relation-extraction", "schema-extraction", "taxonomy", "taxonomy-discovery" ] }, { "id": "phase2-poveda-2014-oops", "title": "OOPS! (OntOlogy Pitfall Scanner!): An On-line Tool for Ontology Evaluation", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2014, "url": "https://doi.org/10.1007/s13740-014-0028-y", "retrieval_tags": [ "automated-quality-check", "ontology-engineering", "ontology-evaluation", "ontology-governance", "oops", "phase16", "pitfalls", "quality", "validation" ] }, { "id": "p2-llm-ont-006", "title": "Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Field", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://doi.org/10.1016/j.ipm.2025.104262", "retrieval_tags": [ "engineering", "engineering-domain", "information-processing-management", "ipm-2026", "llm", "ontology-generation", "phase6", "relation-classification", "scholarly-ontology", "semantic-relations" ] } ] }, { "concept": "ontology_evaluation", "chunk_count": 30, "direct_source_count": 10, "top_sources": [ { "id": "core-uschold-gruninger-1996-principles-methods", "title": "Ontologies: Principles, Methods and Applications", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 1996, "url": "https://doi.org/10.1017/S0269888900007797", "retrieval_tags": [ "competency-questions", "core", "evaluation", "methodology", "ontology-engineering" ] }, { "id": "phase2-kommineni-2024-llm-ontology-kg-construction", "title": "From human experts to machines: An LLM supported approach to ontology and knowledge graph construction", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2403.08345", "retrieval_tags": [ "competency-questions", "core", "evaluation", "human-in-the-loop", "knowledge-graph-construction", "llm", "ontology-construction", "ontology-engineering" ] }, { "id": "core-noy-mcguinness-2001-ontology-101", "title": "Ontology Development 101: A Guide to Creating Your First Ontology", "bucket": "technical", "quality_signal": "widely_cited", "triage_tier": "core", "year": 2001, "url": "https://protege.stanford.edu/publications/ontology_development/ontology101.pdf", "retrieval_tags": [ "classes", "core", "ontology-development", "ontology-engineering", "properties", "protege", "slots", "tutorial" ] }, { "id": "p2-llm-ont-005", "title": "Ontology Generation using Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://dl.acm.org/doi/10.1007/978-3-031-94575-5_18", "retrieval_tags": [ "competency-questions", "evaluation", "llm", "ontogenia", "ontology-generation", "owl" ] }, { "id": "phase2-poveda-2014-oops", "title": "OOPS! (OntOlogy Pitfall Scanner!): An On-line Tool for Ontology Evaluation", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2014, "url": "https://doi.org/10.1007/s13740-014-0028-y", "retrieval_tags": [ "automated-quality-check", "ontology-engineering", "ontology-evaluation", "ontology-governance", "oops", "phase16", "pitfalls", "quality", "validation" ] }, { "id": "oa-https-openalex-org-w1563421732", "title": "Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web", "bucket": "academic", "quality_signal": "scholarly_index", "triage_tier": "candidate", "year": 2004, "url": "https://openalex.org/W1563421732", "retrieval_tags": [ "foundational", "openalex" ] }, { "id": "p2-llm-ont-008", "title": "A RAG Approach for Generating Competency Questions in Ontology Engineering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://arxiv.org/abs/2409.08820", "retrieval_tags": [ "competency-questions", "llm", "mtsr-2024", "ontology-requirements", "rag" ] }, { "id": "phase6-lippolis-2025-llm-assisting-ontology-evaluation", "title": "Large Language Models Assisting Ontology Evaluation", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://doi.org/10.1007/978-3-032-09527-5_27", "retrieval_tags": [ "competency-questions", "evaluation", "iswc-2025", "llm", "ontology-engineering", "ontology-evaluation", "phase6", "validation" ] } ] }, { "concept": "ontology_quality", "chunk_count": 113, "direct_source_count": 29, "top_sources": [ { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "core-gao-2023-rag-survey", "title": "Retrieval-Augmented Generation for Large Language Models: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2312.10997", "retrieval_tags": [ "advanced-rag", "core", "evaluation", "llm", "rag", "retrieval", "retrieval-pipeline", "survey" ] }, { "id": "core-edge-2024-graphrag", "title": "From Local to Global: A Graph RAG Approach to Query-Focused Summarization", "bucket": "academic", "quality_signal": "primary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2404.16130", "retrieval_tags": [ "community-summary", "core", "enterprise-search", "evaluation", "graphrag", "knowledge-graph", "microsoft", "private-data", "provenance", "query-focused-summarization", "rag", "retrieval" ] }, { "id": "oa-https-doi-org-10-3233-sw-140134", "title": "DBpedia – A large-scale, multilingual knowledge base extracted from Wikipedia", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2015, "url": "https://doi.org/10.3233/SW-140134", "retrieval_tags": [ "commercial", "core", "dbpedia", "foundational", "knowledge-graph", "linked-data", "openalex" ] }, { "id": "core-gene-ontology-2000", "title": "Gene Ontology: Tool for the Unification of Biology", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 2000, "url": "https://doi.org/10.1038/75556", "retrieval_tags": [ "annotation", "biology", "biomedical-ontology", "controlled-vocabulary", "core", "data-integration", "gene-ontology", "scientific-infrastructure" ] }, { "id": "pal-sec-2025-10k-2026", "title": "Palantir Technologies Inc. Form 10-K for fiscal year ended December 31, 2025", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://www.sec.gov/Archives/edgar/data/1321655/000132165526000011/pltr-20251231.htm", "retrieval_tags": [ "10-k", "aip", "foundry", "investor", "ontology", "palantir", "revenue", "risk-factors", "sec" ] }, { "id": "phase4-std-dpv-2-0-2024", "title": "Data Privacy Vocabulary (DPV) Version 2.0", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://www.w3.org/community/reports/dpvcg/CG-FINAL-dpv-20240801", "retrieval_tags": [ "compliance", "data-governance", "dpv", "gdpr", "ontology-governance", "phase16", "policy-vocabulary", "privacy", "privacy-vocabulary", "risk", "semantic-interoperability", "w3c-community" ] }, { "id": "phase16-solid-protocol-linked-data-pods-2025", "title": "Solid Protocol", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://solidproject.org/TR/protocol", "retrieval_tags": [ "access-control", "decentralized-data", "federated-data-sharing", "linked-data", "ontology-governance", "phase16", "solid", "solid-pods" ] } ] }, { "concept": "ontology_evolution", "chunk_count": 19, "direct_source_count": 7, "top_sources": [ { "id": "oa-https-doi-org-10-3390-electronics14183583", "title": "ForestGPT and Beyond: A Trustworthy Domain-Specific Large Language Model Paving the Way to Forestry 5.0", "bucket": "palantir", "quality_signal": "scholarly_index", "triage_tier": "core", "year": 2025, "url": "https://openalex.org/W4414098962", "retrieval_tags": [ "openalex", "palantir" ] }, { "id": "phase16-noy-klein-2004-ontology-evolution-schema-evolution", "title": "Ontology Evolution: Not the Same as Schema Evolution", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 2004, "url": "https://www.sciencedirect.com/science/article/pii/S1570826804000224", "retrieval_tags": [ "change-management", "ontology-evolution", "ontology-governance", "ontology-maintenance", "ontology-versioning", "phase16", "schema-evolution", "semantic-drift" ] }, { "id": "phase7-ontology-development-kit-toolkit-2022", "title": "Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2022, "url": "https://doi.org/10.1093/database/baac087", "retrieval_tags": [ "biomedical-ontology", "maintenance", "obo", "ontology-development-kit", "ontology-engineering", "phase7", "reproducibility", "tooling" ] }, { "id": "phase7-gene-ontology-knowledgebase-2023", "title": "The Gene Ontology knowledgebase in 2023", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://doi.org/10.1093/genetics/iyad031", "retrieval_tags": [ "biology", "biomedical-ontology", "gene-ontology", "go-cam", "ontology-infrastructure", "phase7", "scientific-infrastructure", "validation" ] }, { "id": "phase4-nature-noy-2019-industry-scale-kgs", "title": "Industry-Scale Knowledge Graphs: Lessons and Challenges", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2019, "url": "https://doi.org/10.1145/3331166", "retrieval_tags": [ "data-integration", "entity-resolution", "industrial-ai", "knowledge-graph", "schema-evolution" ] }, { "id": "s2-10-1109-access-2026-3702066", "title": "A Review of Neuro-Symbolic AI for Smart Cities: Architectures, Ontologies, and IoT-Driven Applications", "bucket": "academic", "quality_signal": "scholarly_index", "triage_tier": "candidate", "year": 2026, "url": "https://www.semanticscholar.org/paper/26ca9e17166ddf809fa2142520d4734514b14872", "retrieval_tags": [ "ontology_ai", "semantic-scholar" ] }, { "id": "suarez_figueroa_2015_neon", "title": "A Scenario-Based Methodology for Ontology Development", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "low_priority", "year": 2015, "url": "https://doi.org/10.3233/AO-150145", "retrieval_tags": [ "collaborative-ontology", "methodology", "neon", "ontology-engineering", "ontology-governance", "ontology-networks", "phase16", "reengineering", "reuse" ] } ] }, { "concept": "ontology_reporting", "chunk_count": 15, "direct_source_count": 6, "top_sources": [ { "id": "phase14-croissant-ml-ready-dataset-metadata-2024", "title": "Croissant: A Metadata Format for ML-Ready Datasets", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2024, "url": "https://doi.org/10.1145/3650203.3663326", "retrieval_tags": [ "croissant", "dataset-metadata", "json-ld", "machine-learning-data", "ml-ready-data", "phase14", "responsible-ai", "schema-org", "semantic-interoperability" ] }, { "id": "phase2-benchmarking-agents-2025", "title": "Benchmarking Agentic AI Systems: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2025, "url": "https://arxiv.org/abs/2503.16416", "retrieval_tags": [ "agent-memory", "agents", "benchmark", "evaluation", "governance", "mcp", "tool-use" ] }, { "id": "phase16-miro-guidelines-minimum-information-reporting-ontology-2017", "title": "MIRO: Guidelines for Minimum Information for the Reporting of an Ontology", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2017, "url": "https://doi.org/10.1186/s13326-017-0172-7", "retrieval_tags": [ "documentation", "miro", "ontology-evaluation", "ontology-governance", "ontology-reporting", "phase16", "reporting-guidelines", "reproducibility" ] }, { "id": "phase7-ontology-development-kit-toolkit-2022", "title": "Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2022, "url": "https://doi.org/10.1093/database/baac087", "retrieval_tags": [ "biomedical-ontology", "maintenance", "obo", "ontology-development-kit", "ontology-engineering", "phase7", "reproducibility", "tooling" ] }, { "id": "phase7-gene-ontology-knowledgebase-2023", "title": "The Gene Ontology knowledgebase in 2023", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://doi.org/10.1093/genetics/iyad031", "retrieval_tags": [ "biology", "biomedical-ontology", "gene-ontology", "go-cam", "ontology-infrastructure", "phase7", "scientific-infrastructure", "validation" ] }, { "id": "oa-https-doi-org-10-1093-nar-gkaa1113", "title": "The Gene Ontology resource: enriching a GOld mine", "bucket": "academic", "quality_signal": "scholarly_index", "triage_tier": "candidate", "year": 2020, "url": "https://openalex.org/W3112600195", "retrieval_tags": [ "foundational", "openalex" ] } ] }, { "concept": "semantic_schema", "chunk_count": 18, "direct_source_count": 4, "top_sources": [ { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "phase14-croissant-ml-ready-dataset-metadata-2024", "title": "Croissant: A Metadata Format for ML-Ready Datasets", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2024, "url": "https://doi.org/10.1145/3650203.3663326", "retrieval_tags": [ "croissant", "dataset-metadata", "json-ld", "machine-learning-data", "ml-ready-data", "phase14", "responsible-ai", "schema-org", "semantic-interoperability" ] }, { "id": "phase14-linkml-open-data-modeling-framework-2026", "title": "LinkML: an open data modeling framework", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://doi.org/10.1093/gigascience/giaf152", "retrieval_tags": [ "data-modeling", "fair-data", "linkml", "machine-actionable-schema", "ontology-engineering", "phase14", "schema-language", "semantic-interoperability", "validation" ] }, { "id": "phase14-schemaorg-evolution-structured-data-web-2016", "title": "Schema.org: Evolution of Structured Data on the Web", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2016, "url": "https://doi.org/10.1145/2857274.2857276", "retrieval_tags": [ "common-vocabulary", "lightweight-ontology", "phase14", "schema-org", "semantic-web", "structured-data", "web-scale-semantics" ] } ] }, { "concept": "ontology_mapping_metadata", "chunk_count": 9, "direct_source_count": 2, "top_sources": [ { "id": "phase14-sssom-ontological-mappings-2022", "title": "A Simple Standard for Sharing Ontological Mappings (SSSOM)", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2022, "url": "https://doi.org/10.1093/database/baac035", "retrieval_tags": [ "alignment", "fair-data", "mapping-metadata", "ontology-mapping", "phase14", "schema-alignment", "semantic-interoperability", "sssom" ] }, { "id": "phase7-monarch-initiative-2024", "title": "The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://doi.org/10.1093/nar/gkad1082", "retrieval_tags": [ "biomedical-ontology", "disease", "genes", "knowledge-graph", "monarch", "phase7", "phenotype", "scientific-infrastructure" ] } ] }, { "concept": "ml_dataset_metadata", "chunk_count": 10, "direct_source_count": 2, "top_sources": [ { "id": "phase15-gaiax-ontology-compliance-policy-reasoning-2023", "title": "The Role of Ontologies in Gaia-X", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2023, "url": "https://gaia-x.eu/the-role-of-ontologies-in-gaia-x", "retrieval_tags": [ "compliance", "data-space", "gaia-x", "json-ld", "ontology-governance", "phase15", "policy-reasoning", "shacl", "verifiable-credentials" ] }, { "id": "phase14-croissant-ml-ready-dataset-metadata-2024", "title": "Croissant: A Metadata Format for ML-Ready Datasets", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2024, "url": "https://doi.org/10.1145/3650203.3663326", "retrieval_tags": [ "croissant", "dataset-metadata", "json-ld", "machine-learning-data", "ml-ready-data", "phase14", "responsible-ai", "schema-org", "semantic-interoperability" ] } ] }, { "concept": "open_knowledge_graph", "chunk_count": 10, "direct_source_count": 2, "top_sources": [ { "id": "phase2-graphrag-017", "title": "Ontology-grounded Automatic Knowledge Graph Construction by LLM under Wikidata schema", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://arxiv.org/abs/2412.20942", "retrieval_tags": [ "kg-construction", "knowledge-graph-construction", "llm", "llm-extraction", "ontology-grounded-extraction", "ontology-grounded-kg", "schema-constraints", "wikidata", "wikidata-schema" ] }, { "id": "phase14-wikidata-free-collaborative-knowledgebase-2014", "title": "Wikidata: a free collaborative knowledgebase", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2014, "url": "https://doi.org/10.1145/2629489", "retrieval_tags": [ "collaborative-knowledgebase", "entity-grounding", "knowledge-graph", "open-knowledge-graph", "phase14", "wikidata" ] } ] }, { "concept": "ontology_based_data_access", "chunk_count": 10, "direct_source_count": 3, "top_sources": [ { "id": "core-gao-2023-rag-survey", "title": "Retrieval-Augmented Generation for Large Language Models: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2312.10997", "retrieval_tags": [ "advanced-rag", "core", "evaluation", "llm", "rag", "retrieval", "retrieval-pipeline", "survey" ] }, { "id": "phase14-xiao-2018-ontology-based-data-access-survey", "title": "Ontology-Based Data Access: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2018, "url": "https://www.ijcai.org/proceedings/2018/0777.pdf", "retrieval_tags": [ "data-integration", "obda", "ontology-based-data-access", "phase14", "query-rewriting", "semantic-layer", "virtual-knowledge-graph" ] }, { "id": "phase14-calvanese-2016-ontop-answering-sparql-relational-databases", "title": "Ontop: Answering SPARQL queries over relational databases", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2016, "url": "https://doi.org/10.3233/SW-160217", "retrieval_tags": [ "ontology-based-data-access", "ontop", "phase14", "rdf", "semantic-layer", "sparql", "virtual-knowledge-graph" ] } ] }, { "concept": "virtual_knowledge_graph", "chunk_count": 7, "direct_source_count": 3, "top_sources": [ { "id": "industry-commercial-stardog-virtual-graphs", "title": "Stardog Virtual Graphs documentation", "bucket": "commercial", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://docs.stardog.com/virtual-graphs", "retrieval_tags": [ "data-virtualization", "enterprise-kg", "implementation-evidence", "rdf", "semantic-layer", "sparql", "stardog", "virtual-graph", "virtual-graphs" ] }, { "id": "p2-llm-ont-030", "title": "Integrating Large Language Models and Knowledge Graphs for Extraction and Validation of Textual Test Data", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://arxiv.org/abs/2408.01700", "retrieval_tags": [ "industrial-ai", "iswc-2024", "knowledge-graph", "llm", "ontology-guided-extraction" ] }, { "id": "phase14-calvanese-2016-ontop-answering-sparql-relational-databases", "title": "Ontop: Answering SPARQL queries over relational databases", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2016, "url": "https://doi.org/10.3233/SW-160217", "retrieval_tags": [ "ontology-based-data-access", "ontop", "phase14", "rdf", "semantic-layer", "sparql", "virtual-knowledge-graph" ] } ] }, { "concept": "mapping_language", "chunk_count": 27, "direct_source_count": 6, "top_sources": [ { "id": "phase15-w3c-direct-mapping-relational-data-rdf-2012", "title": "A Direct Mapping of Relational Data to RDF", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2012, "url": "https://www.w3.org/TR/rdb-direct-mapping", "retrieval_tags": [ "data-integration", "direct-mapping", "knowledge-graph-construction", "mapping-language", "phase15", "rdf", "relational-data", "w3c" ] }, { "id": "phase4-std-w3c-r2rml-2012", "title": "R2RML: RDB to RDF Mapping Language", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2012, "url": "https://www.w3.org/TR/r2rml", "retrieval_tags": [ "data-integration", "knowledge-graph", "knowledge-graph-construction", "mapping-language", "mappings", "phase15", "r2rml", "rdf", "relational-data", "w3c" ] }, { "id": "phase15-rml-specification-heterogeneous-rdf-mapping-2024", "title": "RDF Mapping Language (RML)", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://rml.io/specs/rml", "retrieval_tags": [ "data-integration", "heterogeneous-data", "knowledge-graph-construction", "mapping-language", "phase15", "rdf", "rml", "semantic-interoperability" ] }, { "id": "phase15-yarrrml-human-readable-rdf-generation-rules-2025", "title": "YARRRML: Human Readable Text-Based Representation for Declarative Generation Rules", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://w3id.org/yarrrml/spec", "retrieval_tags": [ "data-integration", "knowledge-graph-construction", "mapping-language", "phase15", "rdf", "rml", "semantic-interoperability", "yaml", "yarrrml" ] }, { "id": "phase15-dimou-2014-rml-integrated-rdf-mappings", "title": "RML: A Generic Language for Integrated RDF Mappings of Heterogeneous Data", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2014, "url": "https://ceur-ws.org/Vol-1184/ldow2014_paper_01.pdf", "retrieval_tags": [ "data-integration", "heterogeneous-data", "knowledge-graph-construction", "mapping-language", "phase15", "rdf", "rml", "semantic-interoperability" ] }, { "id": "phase15-arenas-2024-morph-kgc-scalable-kg-materialization", "title": "Morph-KGC: Scalable knowledge graph materialization with mapping partitions", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://doi.org/10.3233/SW-223135", "retrieval_tags": [ "heterogeneous-data", "knowledge-graph-construction", "mapping-language", "morph-kgc", "phase15", "rdf", "rml", "scalable-kg-construction" ] } ] }, { "concept": "knowledge_graph_construction_pipeline", "chunk_count": 23, "direct_source_count": 11, "top_sources": [ { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "arxiv-2306-08302v3", "title": "Unifying Large Language Models and Knowledge Graphs: A Roadmap", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2306.08302", "retrieval_tags": [ "arxiv", "core", "grounding", "hybrid-ai", "knowledge-graph", "large-language-models", "llm", "llm-kg", "ontology_ai", "reasoning", "roadmap", "survey" ] }, { "id": "phase2-kommineni-2024-llm-ontology-kg-construction", "title": "From human experts to machines: An LLM supported approach to ontology and knowledge graph construction", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2403.08345", "retrieval_tags": [ "competency-questions", "core", "evaluation", "human-in-the-loop", "knowledge-graph-construction", "llm", "ontology-construction", "ontology-engineering" ] }, { "id": "industry-commercial-poolparty-suite", "title": "PoolParty Semantic Suite product and documentation materials", "bucket": "commercial", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.poolparty.biz/products/semantic-suite", "retrieval_tags": [ "entity-extraction", "poolparty", "semantic-ai", "semantic-search", "skos", "taxonomy" ] }, { "id": "phase15-rml-specification-heterogeneous-rdf-mapping-2024", "title": "RDF Mapping Language (RML)", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://rml.io/specs/rml", "retrieval_tags": [ "data-integration", "heterogeneous-data", "knowledge-graph-construction", "mapping-language", "phase15", "rdf", "rml", "semantic-interoperability" ] }, { "id": "phase3-llm-ontmem-023", "title": "LLM-empowered Knowledge Graph Construction: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2025, "url": "https://arxiv.org/abs/2510.20345", "retrieval_tags": [ "graph-quality", "knowledge-graph-construction", "llm", "schema-guidance", "survey" ] }, { "id": "p2-llm-ont-021", "title": "Large Language Models and Knowledge Graphs: Opportunities and Challenges", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.2", "retrieval_tags": [ "hybrid-knowledge", "knowledge-graph", "llm", "ontology", "tgdk" ] }, { "id": "phase15-arenas-2024-morph-kgc-scalable-kg-materialization", "title": "Morph-KGC: Scalable knowledge graph materialization with mapping partitions", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://doi.org/10.3233/SW-223135", "retrieval_tags": [ "heterogeneous-data", "knowledge-graph-construction", "mapping-language", "morph-kgc", "phase15", "rdf", "rml", "scalable-kg-construction" ] } ] }, { "concept": "data_space", "chunk_count": 22, "direct_source_count": 4, "top_sources": [ { "id": "phase15-dataspace-protocol-2025-1", "title": "Dataspace Protocol 2025-1", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2025, "url": "https://eclipse-dataspace-protocol-base.github.io/DataspaceProtocol/2025-1", "retrieval_tags": [ "agreement-negotiation", "data-space", "dataspace-protocol", "dataspaces", "federated-data-sharing", "phase15", "usage-control", "usage-policy" ] }, { "id": "phase15-idsa-semantic-interoperability-data-spaces-2024", "title": "Semantic Interoperability in Data Spaces", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://zenodo.org/records/10964377", "retrieval_tags": [ "data-governance", "data-sovereignty", "data-space", "dataspaces", "idsa", "phase15", "semantic-interoperability", "usage-policy" ] }, { "id": "p2-llm-ont-031", "title": "From Instructions to ODRL Usage Policies: An Ontology Guided Approach", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://arxiv.org/abs/2506.03301", "retrieval_tags": [ "dataspaces", "llm", "odrl", "ontology-guided-generation", "usage-policy" ] }, { "id": "phase15-ids-information-model-ontology-2020", "title": "The International Data Spaces Information Model - An Ontology for Sovereign Exchange of Digital Content", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2020, "url": "https://doi.org/10.1007/978-3-030-62466-8_12", "retrieval_tags": [ "data-sovereignty", "data-space", "dataspaces", "ids-information-model", "ontology", "phase15", "semantic-interoperability", "usage-policy" ] } ] }, { "concept": "federated_data_sharing", "chunk_count": 8, "direct_source_count": 5, "top_sources": [ { "id": "phase15-dataspace-protocol-2025-1", "title": "Dataspace Protocol 2025-1", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2025, "url": "https://eclipse-dataspace-protocol-base.github.io/DataspaceProtocol/2025-1", "retrieval_tags": [ "agreement-negotiation", "data-space", "dataspace-protocol", "dataspaces", "federated-data-sharing", "phase15", "usage-control", "usage-policy" ] }, { "id": "phase16-eclass-rdf-owl-product-classification", "title": "eCl@ss in RDF/OWL", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://www.eclass.eu/en/standard/eclassrdfowl", "retrieval_tags": [ "eclass", "industrial-semantic-standards", "ontology-governance", "phase16", "product-classification", "rdf", "semantic-interoperability", "supply-chain" ] }, { "id": "phase15-idsa-semantic-interoperability-data-spaces-2024", "title": "Semantic Interoperability in Data Spaces", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://zenodo.org/records/10964377", "retrieval_tags": [ "data-governance", "data-sovereignty", "data-space", "dataspaces", "idsa", "phase15", "semantic-interoperability", "usage-policy" ] }, { "id": "phase15-ids-information-model-ontology-2020", "title": "The International Data Spaces Information Model - An Ontology for Sovereign Exchange of Digital Content", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2020, "url": "https://doi.org/10.1007/978-3-030-62466-8_12", "retrieval_tags": [ "data-sovereignty", "data-space", "dataspaces", "ids-information-model", "ontology", "phase15", "semantic-interoperability", "usage-policy" ] }, { "id": "phase3-n3c-governance-ecosystem-2023", "title": "The N3C governance ecosystem: A model socio-technical partnership for large-scale health data sharing", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10789985", "retrieval_tags": [ "data-enclave", "governance", "health-data-sharing", "n3c", "socio-technical" ] } ] }, { "concept": "compliance_policy_reasoning", "chunk_count": 24, "direct_source_count": 6, "top_sources": [ { "id": "pal-pcl-2026", "title": "Privacy and Civil Liberties", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/pcl", "retrieval_tags": [ "civil-liberties", "governance", "palantir", "privacy", "public-sector", "public-trust" ] }, { "id": "phase4-std-dpv-2-0-2024", "title": "Data Privacy Vocabulary (DPV) Version 2.0", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://www.w3.org/community/reports/dpvcg/CG-FINAL-dpv-20240801", "retrieval_tags": [ "compliance", "data-governance", "dpv", "gdpr", "ontology-governance", "phase16", "policy-vocabulary", "privacy", "privacy-vocabulary", "risk", "semantic-interoperability", "w3c-community" ] }, { "id": "phase15-gaiax-ontology-compliance-policy-reasoning-2023", "title": "The Role of Ontologies in Gaia-X", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2023, "url": "https://gaia-x.eu/the-role-of-ontologies-in-gaia-x", "retrieval_tags": [ "compliance", "data-space", "gaia-x", "json-ld", "ontology-governance", "phase15", "policy-reasoning", "shacl", "verifiable-credentials" ] }, { "id": "oa-https-doi-org-10-36227-techrxiv-175624549-98427022-v1", "title": "Enterprise Digital Twins in Financial Services: Convergence of Architecture, Operations, and Engineering", "bucket": "palantir", "quality_signal": "scholarly_index", "triage_tier": "core", "year": 2025, "url": "https://openalex.org/W4413638561", "retrieval_tags": [ "openalex", "palantir" ] }, { "id": "s2-10-30574-wjaets-2026-19-1-0172", "title": "A multi-layer governance architecture for enterprise generative AI systems", "bucket": "academic", "quality_signal": "scholarly_index", "triage_tier": "candidate", "year": 2026, "url": "https://www.semanticscholar.org/paper/2b6bf2d07e9ef4928003c29a0ed989fdf225b300", "retrieval_tags": [ "commercial", "semantic-scholar" ] }, { "id": "phase11-tuan-sanyal-2026-ontology-constrained-neural-reasoning-enterprise-agents", "title": "Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2604.00555", "retrieval_tags": [ "agentic-ai", "domain-grounded-ai", "domain-ontology", "enterprise-agents", "governance", "governed-action", "interaction-ontology", "neurosymbolic", "neurosymbolic-ai", "ontology-constrained-reasoning", "phase11", "phase5" ] } ] }, { "concept": "machine_actionable_metadata", "chunk_count": 8, "direct_source_count": 3, "top_sources": [ { "id": "phase14-fair-data-point-metadata-publication-2023", "title": "FAIR Data Point: A FAIR-Oriented Approach for Metadata Publication", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://doi.org/10.1162/dint_a_00160", "retrieval_tags": [ "dcat", "fair-data", "fair-data-point", "linked-data", "machine-actionable-metadata", "metadata-service", "phase14", "semantic-interoperability" ] }, { "id": "wilkinson_etal_2016_fair", "title": "The FAIR Guiding Principles for Scientific Data Management and Stewardship", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2016, "url": "https://doi.org/10.1038/sdata.2016.18", "retrieval_tags": [ "data-stewardship", "fair", "interoperability", "metadata", "reuse" ] }, { "id": "phase14-fair-digital-object-conceptual-model-2023", "title": "Towards a Conceptual Model for the FAIR Digital Object Framework", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "low_priority", "year": 2023, "url": "https://arxiv.org/abs/2302.11894", "retrieval_tags": [ "fair-data", "fair-digital-object", "machine-actionable-metadata", "ontology-driven-model", "persistent-identifier", "phase14" ] } ] }, { "concept": "fair_digital_object", "chunk_count": 5, "direct_source_count": 1, "top_sources": [ { "id": "phase14-fair-digital-object-conceptual-model-2023", "title": "Towards a Conceptual Model for the FAIR Digital Object Framework", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "low_priority", "year": 2023, "url": "https://arxiv.org/abs/2302.11894", "retrieval_tags": [ "fair-data", "fair-digital-object", "machine-actionable-metadata", "ontology-driven-model", "persistent-identifier", "phase14" ] } ] }, { "concept": "curated_knowledge_infrastructure", "chunk_count": 11, "direct_source_count": 4, "top_sources": [ { "id": "core-gene-ontology-2000", "title": "Gene Ontology: Tool for the Unification of Biology", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 2000, "url": "https://doi.org/10.1038/75556", "retrieval_tags": [ "annotation", "biology", "biomedical-ontology", "controlled-vocabulary", "core", "data-integration", "gene-ontology", "scientific-infrastructure" ] }, { "id": "phase16-fairsharing-community-standards-repositories-policies-2019", "title": "FAIRsharing as a Community Approach to Standards, Repositories and Policies", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2019, "url": "https://doi.org/10.1038/s41587-019-0080-8", "retrieval_tags": [ "curated-knowledge-infrastructure", "fair-data", "fairsharing", "metadata-standards", "ontology-governance", "phase16", "repositories", "standards-registry" ] }, { "id": "phase14-hoyt-gyori-2024-o3-guidelines-curated-resources", "title": "The O3 guidelines: open data, open code, and open infrastructure for sustainable curated scientific resources", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://doi.org/10.1038/s41597-024-03406-w", "retrieval_tags": [ "community-curation", "knowledge-infrastructure", "o3-guidelines", "open-code", "open-data", "open-infrastructure", "phase14", "scientific-infrastructure" ] }, { "id": "phase7-human-phenotype-ontology-2024", "title": "The Human Phenotype Ontology in 2024: phenotypes around the world", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://doi.org/10.1093/nar/gkad1005", "retrieval_tags": [ "biomedical-ontology", "clinical-ai", "diagnosis", "hpo", "ontology-infrastructure", "phase7", "phenotype", "scientific-infrastructure" ] } ] }, { "concept": "llm_kg", "chunk_count": 545, "direct_source_count": 108, "top_sources": [ { "id": "phase2-pal-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluate Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "core", "custom-evaluation", "governed-action", "ontology-edits", "palantir", "simulation", "validation", "write-capable-agents" ] }, { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "oa-https-doi-org-10-1109-tnnls-2021-3070843", "title": "A Survey on Knowledge Graphs: Representation, Acquisition, and Applications", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://ieeexplore.ieee.org/document/9416312", "retrieval_tags": [ "applications", "core", "foundational", "kg-completion", "knowledge-acquisition", "knowledge-graph", "ontology_ai", "openalex", "representation-learning", "survey" ] }, { "id": "core-gao-2023-rag-survey", "title": "Retrieval-Augmented Generation for Large Language Models: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2312.10997", "retrieval_tags": [ "advanced-rag", "core", "evaluation", "llm", "rag", "retrieval", "retrieval-pipeline", "survey" ] }, { "id": "arxiv-2306-08302v3", "title": "Unifying Large Language Models and Knowledge Graphs: A Roadmap", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2306.08302", "retrieval_tags": [ "arxiv", "core", "grounding", "hybrid-ai", "knowledge-graph", "large-language-models", "llm", "llm-kg", "ontology_ai", "reasoning", "roadmap", "survey" ] }, { "id": "phase2-w3c-prov-o-2013", "title": "PROV-O: The PROV Ontology", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://www.w3.org/TR/prov-o", "retrieval_tags": [ "audit", "core", "lineage", "owl", "prov-o", "provenance", "trustworthy-ai", "w3c" ] }, { "id": "phase2-iso-iec-42001-2023", "title": "ISO/IEC 42001:2023 Artificial intelligence - Management system", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2023, "url": "https://www.iso.org/standard/81230.html", "retrieval_tags": [ "ai-management-system", "core", "governance", "iso", "lifecycle", "policy", "risk-management" ] } ] }, { "concept": "rag", "chunk_count": 243, "direct_source_count": 35, "top_sources": [ { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "core-gao-2023-rag-survey", "title": "Retrieval-Augmented Generation for Large Language Models: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2312.10997", "retrieval_tags": [ "advanced-rag", "core", "evaluation", "llm", "rag", "retrieval", "retrieval-pipeline", "survey" ] }, { "id": "core-edge-2024-graphrag", "title": "From Local to Global: A Graph RAG Approach to Query-Focused Summarization", "bucket": "academic", "quality_signal": "primary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2404.16130", "retrieval_tags": [ "community-summary", "core", "enterprise-search", "evaluation", "graphrag", "knowledge-graph", "microsoft", "private-data", "provenance", "query-focused-summarization", "rag", "retrieval" ] }, { "id": "phase2-gutierrez-2025-hipporag2", "title": "From RAG to Memory: Non-Parametric Continual Learning for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2025, "url": "https://arxiv.org/abs/2502.14802", "retrieval_tags": [ "agent-memory", "continual-learning", "core", "graph-rag", "hipporag", "knowledge-graph", "memory", "non-parametric-memory", "rag" ] }, { "id": "core-lewis-2020-rag", "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 2020, "url": "https://arxiv.org/abs/2005.11401", "retrieval_tags": [ "core", "evidence", "external-memory", "grounding", "knowledge-intensive", "knowledge-intensive-nlp", "llm", "rag", "retrieval", "retrieval-augmented-generation" ] }, { "id": "phase2-he-2024-g-retriever", "title": "G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2402.07630", "retrieval_tags": [ "core", "g-retriever", "graph-qa", "graph-rag", "hallucination", "knowledge-graph", "rag", "retrieval", "subgraph-retrieval", "textual-graphs" ] }, { "id": "ont-ai-023", "title": "HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2405.14831", "retrieval_tags": [ "agent-memory", "associative-memory", "core", "graph-retrieval", "hipporag", "knowledge-graph", "llm", "long-term-memory", "multi-hop", "multi-hop-qa", "neurips-2024", "pagerank" ] }, { "id": "ont-ai-022", "title": "LightRAG: Simple and Fast Retrieval-Augmented Generation", "bucket": "academic", "quality_signal": "secondary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2410.05779", "retrieval_tags": [ "core", "efficient-rag", "graph-rag", "graphrag", "incremental-update", "knowledge-graph", "lightrag", "llm", "local-global-retrieval", "rag", "retrieval", "structured-retrieval" ] } ] }, { "concept": "ontology_grounded_rag", "chunk_count": 6, "direct_source_count": 3, "top_sources": [ { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "phase6-sharma-2025-og-rag", "title": "OG-RAG: Ontology-Grounded Retrieval-Augmented Generation for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://aclanthology.org/2025.emnlp-main.1674", "retrieval_tags": [ "domain-ontology", "emnlp-2025", "graphrag", "hypergraph-retrieval", "og-rag", "ontology-grounded-rag", "phase6", "rag" ] }, { "id": "phase6-oarga-2026-scientific-kg-ontology-open-llms", "title": "Scientific Knowledge Graph and Ontology Generation Using Open Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://pubs.rsc.org/en/content/articlelanding/2026/dd/d5dd00275c", "retrieval_tags": [ "digital-discovery-2026", "graphrag", "knowledge-graph", "llm", "ontology-generation", "open-llm", "phase6", "scientific-kg" ] } ] }, { "concept": "hallucination_mitigation", "chunk_count": 44, "direct_source_count": 13, "top_sources": [ { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "phase2-he-2024-g-retriever", "title": "G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2402.07630", "retrieval_tags": [ "core", "g-retriever", "graph-qa", "graph-rag", "hallucination", "knowledge-graph", "rag", "retrieval", "subgraph-retrieval", "textual-graphs" ] }, { "id": "pal-blog-rag-oag-2023", "title": "Building with Palantir AIP: Data Tools for RAG / OAG", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2023, "url": "https://blog.palantir.com/building-with-palantir-aip-data-tools-for-rag-oag-b3b509c8b0f3", "retrieval_tags": [ "aip", "llm", "llm-grounding", "oag", "ontology-augmented-generation", "palantir", "palantir-blog", "rag" ] }, { "id": "oa-https-doi-org-10-3390-electronics14183583", "title": "ForestGPT and Beyond: A Trustworthy Domain-Specific Large Language Model Paving the Way to Forestry 5.0", "bucket": "palantir", "quality_signal": "scholarly_index", "triage_tier": "core", "year": 2025, "url": "https://openalex.org/W4414098962", "retrieval_tags": [ "openalex", "palantir" ] }, { "id": "phase3-llm-ontmem-023", "title": "LLM-empowered Knowledge Graph Construction: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2025, "url": "https://arxiv.org/abs/2510.20345", "retrieval_tags": [ "graph-quality", "knowledge-graph-construction", "llm", "schema-guidance", "survey" ] }, { "id": "phase6-sui-2025-fidelis-kgqa", "title": "FiDeLiS: Faithful Reasoning in Large Language Models for Knowledge Graph Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://aclanthology.org/2025.findings-acl.436", "retrieval_tags": [ "acl-2025", "faithful-reasoning", "kgqa", "knowledge-graph", "phase6", "reasoning-paths", "structured-grounding" ] }, { "id": "phase11-ali-2026-ontology-grounded-kg-clinical-hallucinations", "title": "Ontology-grounded knowledge graphs for mitigating hallucinations in large language models for clinical question answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://doi.org/10.1016/j.jbi.2026.104993", "retrieval_tags": [ "biomedical-ontology", "clinical-qa", "hallucination-mitigation", "knowledge-graph", "llm", "ontology-grounded-rag", "phase11", "rag", "safety-critical-ai" ] }, { "id": "phase11-hamed-rocha-2026-biomedical-rag-majority-voting-verification-protocol", "title": "Protocol for evaluating ChatGPT in biomedical association generation and verification using a RAG-enabled, cross-model majority voting workflow", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://doi.org/10.1016/j.xpro.2026.104533", "retrieval_tags": [ "biomedical-ontology", "biomedical-verification", "cross-model-voting", "evaluation-protocol", "fact-checking", "hallucination-mitigation", "phase11", "rag", "validation" ] } ] }, { "concept": "graphrag", "chunk_count": 155, "direct_source_count": 19, "top_sources": [ { "id": "core-edge-2024-graphrag", "title": "From Local to Global: A Graph RAG Approach to Query-Focused Summarization", "bucket": "academic", "quality_signal": "primary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2404.16130", "retrieval_tags": [ "community-summary", "core", "enterprise-search", "evaluation", "graphrag", "knowledge-graph", "microsoft", "private-data", "provenance", "query-focused-summarization", "rag", "retrieval" ] }, { "id": "phase2-gutierrez-2025-hipporag2", "title": "From RAG to Memory: Non-Parametric Continual Learning for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2025, "url": "https://arxiv.org/abs/2502.14802", "retrieval_tags": [ "agent-memory", "continual-learning", "core", "graph-rag", "hipporag", "knowledge-graph", "memory", "non-parametric-memory", "rag" ] }, { "id": "phase2-he-2024-g-retriever", "title": "G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2402.07630", "retrieval_tags": [ "core", "g-retriever", "graph-qa", "graph-rag", "hallucination", "knowledge-graph", "rag", "retrieval", "subgraph-retrieval", "textual-graphs" ] }, { "id": "ont-ai-022", "title": "LightRAG: Simple and Fast Retrieval-Augmented Generation", "bucket": "academic", "quality_signal": "secondary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2410.05779", "retrieval_tags": [ "core", "efficient-rag", "graph-rag", "graphrag", "incremental-update", "knowledge-graph", "lightrag", "llm", "local-global-retrieval", "rag", "retrieval", "structured-retrieval" ] }, { "id": "ont-ai-024", "title": "KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation", "bucket": "academic", "quality_signal": "secondary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2409.13731", "retrieval_tags": [ "core", "enterprise-ai", "graph-retrieval", "graphrag", "hybrid-retrieval", "kag", "knowledge-augmented-generation", "knowledge-graph", "llm", "logical-form", "openspg", "professional-domain" ] }, { "id": "industry-commercial-allegrograph-llm", "title": "AllegroGraph knowledge graph, vector, and LLM materials", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://allegrograph.com", "retrieval_tags": [ "allegrograph", "graphrag", "llm", "neuro-symbolic", "rdf", "vector-search" ] }, { "id": "phase2-graphrag-032", "title": "LlamaIndex Knowledge Graph RAG documentation", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://docs.llamaindex.ai", "retrieval_tags": [ "developer-tooling", "knowledge-graph-index", "llamaindex", "property-graph", "rag-framework" ] }, { "id": "industry-commercial-neo4j-graphrag-docs", "title": "Neo4j GraphRAG documentation and developer guidance", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://neo4j.com/docs/neo4j-graphrag-python/current", "retrieval_tags": [ "cypher", "graph-traversal", "graphrag", "llm", "neo4j", "property-graph", "vector-search" ] } ] }, { "concept": "memgraphrag", "chunk_count": 2, "direct_source_count": 1, "top_sources": [ { "id": "phase11-wu-2026-memgraphrag-memory-multi-agent-graphrag", "title": "MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2606.00610", "retrieval_tags": [ "agent-memory", "graph-based-memory", "graphrag", "knowledge-graph", "llm", "multi-agent", "phase11", "rag" ] } ] }, { "concept": "kgqa", "chunk_count": 28, "direct_source_count": 10, "top_sources": [ { "id": "oa-https-doi-org-10-1109-tnnls-2021-3070843", "title": "A Survey on Knowledge Graphs: Representation, Acquisition, and Applications", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://ieeexplore.ieee.org/document/9416312", "retrieval_tags": [ "applications", "core", "foundational", "kg-completion", "knowledge-acquisition", "knowledge-graph", "ontology_ai", "openalex", "representation-learning", "survey" ] }, { "id": "arxiv-2306-08302v3", "title": "Unifying Large Language Models and Knowledge Graphs: A Roadmap", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2306.08302", "retrieval_tags": [ "arxiv", "core", "grounding", "hybrid-ai", "knowledge-graph", "large-language-models", "llm", "llm-kg", "ontology_ai", "reasoning", "roadmap", "survey" ] }, { "id": "core-edge-2024-graphrag", "title": "From Local to Global: A Graph RAG Approach to Query-Focused Summarization", "bucket": "academic", "quality_signal": "primary_source", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2404.16130", "retrieval_tags": [ "community-summary", "core", "enterprise-search", "evaluation", "graphrag", "knowledge-graph", "microsoft", "private-data", "provenance", "query-focused-summarization", "rag", "retrieval" ] }, { "id": "phase2-he-2024-g-retriever", "title": "G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2402.07630", "retrieval_tags": [ "core", "g-retriever", "graph-qa", "graph-rag", "hallucination", "knowledge-graph", "rag", "retrieval", "subgraph-retrieval", "textual-graphs" ] }, { "id": "industry-commercial-microsoft-graphrag", "title": "GraphRAG: graph-based retrieval augmented generation", "bucket": "technical", "quality_signal": "primary_source", "triage_tier": "candidate", "year": 2024, "url": "https://github.com/microsoft/graphrag", "retrieval_tags": [ "communities", "entity-extraction", "global-search", "graphrag", "knowledge-graph", "llm", "local-search", "microsoft", "open-source", "retrieval" ] }, { "id": "phase6-sui-2025-fidelis-kgqa", "title": "FiDeLiS: Faithful Reasoning in Large Language Models for Knowledge Graph Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://aclanthology.org/2025.findings-acl.436", "retrieval_tags": [ "acl-2025", "faithful-reasoning", "kgqa", "knowledge-graph", "phase6", "reasoning-paths", "structured-grounding" ] }, { "id": "phase11-ali-2026-ontology-grounded-kg-clinical-hallucinations", "title": "Ontology-grounded knowledge graphs for mitigating hallucinations in large language models for clinical question answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2026, "url": "https://doi.org/10.1016/j.jbi.2026.104993", "retrieval_tags": [ "biomedical-ontology", "clinical-qa", "hallucination-mitigation", "knowledge-graph", "llm", "ontology-grounded-rag", "phase11", "rag", "safety-critical-ai" ] }, { "id": "phase5-liu-2025-ontology-guided-reverse-thinking-kgqa", "title": "Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://aclanthology.org/2025.acl-long.741", "retrieval_tags": [ "acl-2025", "kgqa", "knowledge-graph", "llm", "multi-hop-reasoning", "ontology", "ontology-guided", "phase5", "retrieval" ] } ] }, { "concept": "agent_memory", "chunk_count": 138, "direct_source_count": 18, "top_sources": [ { "id": "core-gao-2023-rag-survey", "title": "Retrieval-Augmented Generation for Large Language Models: A Survey", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2312.10997", "retrieval_tags": [ "advanced-rag", "core", "evaluation", "llm", "rag", "retrieval", "retrieval-pipeline", "survey" ] }, { "id": "phase2-gutierrez-2025-hipporag2", "title": "From RAG to Memory: Non-Parametric Continual Learning for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2025, "url": "https://arxiv.org/abs/2502.14802", "retrieval_tags": [ "agent-memory", "continual-learning", "core", "graph-rag", "hipporag", "knowledge-graph", "memory", "non-parametric-memory", "rag" ] }, { "id": "core-lewis-2020-rag", "title": "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", "bucket": "academic", "quality_signal": "peer_reviewed_seminal", "triage_tier": "core", "year": 2020, "url": "https://arxiv.org/abs/2005.11401", "retrieval_tags": [ "core", "evidence", "external-memory", "grounding", "knowledge-intensive", "knowledge-intensive-nlp", "llm", "rag", "retrieval", "retrieval-augmented-generation" ] }, { "id": "ont-ai-023", "title": "HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2405.14831", "retrieval_tags": [ "agent-memory", "associative-memory", "core", "graph-retrieval", "hipporag", "knowledge-graph", "llm", "long-term-memory", "multi-hop", "multi-hop-qa", "neurips-2024", "pagerank" ] }, { "id": "phase2-agent-om-2023", "title": "Agent-OM: Leveraging LLM Agents for Ontology Matching", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "core", "year": 2023, "url": "https://arxiv.org/abs/2312.00326", "retrieval_tags": [ "agent-memory", "core", "llm-agent", "llm-agents", "oaei", "ontology-matching", "schema-alignment", "semantic-interoperability", "tool-use", "vldb-2025" ] }, { "id": "phase5-palantir-connecting-agents-decisions-2026", "title": "Connecting Agents to Decisions", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://blog.palantir.com/connecting-agents-to-decisions-277dee8ddb40", "retrieval_tags": [ "agent-memory", "agents", "decision-centric", "decision-lineage", "governed-action", "human-agent-workflows", "ontology", "palantir", "phase5", "security", "tool-use", "writeback" ] }, { "id": "industry-commercial-eccenca-corporate-memory", "title": "eccenca Corporate Memory knowledge graph and data product governance materials", "bucket": "commercial", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://eccenca.com/products/corporate-memory", "retrieval_tags": [ "ai-ready-kg", "corporate-memory", "data-products", "eccenca", "semantic-governance", "shacl" ] }, { "id": "phase16-solid-protocol-linked-data-pods-2025", "title": "Solid Protocol", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://solidproject.org/TR/protocol", "retrieval_tags": [ "access-control", "decentralized-data", "federated-data-sharing", "linked-data", "ontology-governance", "phase16", "solid", "solid-pods" ] } ] }, { "concept": "graph_based_memory", "chunk_count": 23, "direct_source_count": 4, "top_sources": [ { "id": "phase2-hu-2024-graphrag-survey", "title": "A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2024, "url": "https://arxiv.org/abs/2501.13958", "retrieval_tags": [ "customized-llm", "domain-adaptation", "evaluation", "graph-memory", "graphrag", "knowledge-graph", "rag", "retrieval", "survey" ] }, { "id": "phase3-llm-ontmem-018", "title": "Graph-based Agent Memory: Taxonomy, Techniques, and Evaluation", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2602.05665", "retrieval_tags": [ "agent-memory", "arxiv-2026", "evaluation", "graph-based-memory", "graph-memory", "llm-agents", "memory-evolution", "memory-retrieval", "phase6", "survey", "temporal-reasoning" ] }, { "id": "phase6-xu-2025-a-mem-agentic-memory", "title": "A-Mem: Agentic Memory for LLM Agents", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://openreview.net/forum?id=FiM0M8gcct", "retrieval_tags": [ "agent-memory", "llm-agents", "long-term-memory", "memory-graph", "neurips-2025", "phase6", "zettelkasten" ] }, { "id": "phase11-wu-2026-memgraphrag-memory-multi-agent-graphrag", "title": "MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2606.00610", "retrieval_tags": [ "agent-memory", "graph-based-memory", "graphrag", "knowledge-graph", "llm", "multi-agent", "phase11", "rag" ] } ] }, { "concept": "ontology_constrained_reasoning", "chunk_count": 25, "direct_source_count": 4, "top_sources": [ { "id": "p2-llm-ont-031", "title": "From Instructions to ODRL Usage Policies: An Ontology Guided Approach", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://arxiv.org/abs/2506.03301", "retrieval_tags": [ "dataspaces", "llm", "odrl", "ontology-guided-generation", "usage-policy" ] }, { "id": "p2-llm-ont-030", "title": "Integrating Large Language Models and Knowledge Graphs for Extraction and Validation of Textual Test Data", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2024, "url": "https://arxiv.org/abs/2408.01700", "retrieval_tags": [ "industrial-ai", "iswc-2024", "knowledge-graph", "llm", "ontology-guided-extraction" ] }, { "id": "phase5-liu-2025-ontology-guided-reverse-thinking-kgqa", "title": "Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2025, "url": "https://aclanthology.org/2025.acl-long.741", "retrieval_tags": [ "acl-2025", "kgqa", "knowledge-graph", "llm", "multi-hop-reasoning", "ontology", "ontology-guided", "phase5", "retrieval" ] }, { "id": "phase11-tuan-sanyal-2026-ontology-constrained-neural-reasoning-enterprise-agents", "title": "Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2604.00555", "retrieval_tags": [ "agentic-ai", "domain-grounded-ai", "domain-ontology", "enterprise-agents", "governance", "governed-action", "interaction-ontology", "neurosymbolic", "neurosymbolic-ai", "ontology-constrained-reasoning", "phase11", "phase5" ] } ] }, { "concept": "runtime_governance", "chunk_count": 4, "direct_source_count": 2, "top_sources": [ { "id": "phase16-oasis-xacml-3-policy-access-control-2013", "title": "eXtensible Access Control Markup Language (XACML) Version 3.0", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://docs.oasis-open.org/xacml/3.0/xacml-3.0-core-spec-os-en.html", "retrieval_tags": [ "access-control", "attribute-based-access-control", "governed-action", "oasis", "ontology-governance", "phase16", "policy-enforcement", "runtime-governance", "xacml" ] }, { "id": "phase11-joshi-2026-deontic-policies-agentic-ai-runtime-governance", "title": "Deontic Policies for Runtime Governance of Agentic AI Systems", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2606.19464", "retrieval_tags": [ "agentic-ai", "deontic-policy", "governed-action", "llm", "ontology-governance", "owl", "phase11", "policy-reasoning", "runtime-governance", "tool-use" ] } ] }, { "concept": "predeployment_assurance", "chunk_count": 3, "direct_source_count": 1, "top_sources": [ { "id": "phase11-tuan-sanyal-2026-predeployment-assurance-ontology-simulation", "title": "Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification", "bucket": "academic", "quality_signal": "preprint_benchmark", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2606.04037", "retrieval_tags": [ "agent-operational-envelope", "agentic-ai", "ai-assurance", "ontology-grounded-simulation", "phase11", "predeployment-assurance", "regulatory-coverage", "trust-certification", "validation" ] } ] }, { "concept": "privacy_vocabulary", "chunk_count": 10, "direct_source_count": 2, "top_sources": [ { "id": "phase4-std-dpv-2-0-2024", "title": "Data Privacy Vocabulary (DPV) Version 2.0", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://www.w3.org/community/reports/dpvcg/CG-FINAL-dpv-20240801", "retrieval_tags": [ "compliance", "data-governance", "dpv", "gdpr", "ontology-governance", "phase16", "policy-vocabulary", "privacy", "privacy-vocabulary", "risk", "semantic-interoperability", "w3c-community" ] }, { "id": "nhs-fdp-privacy-notice-2024", "title": "NHS Federated Data Platform privacy notice", "bucket": "technical", "quality_signal": "primary_source", "triage_tier": "core", "year": 2024, "url": "https://www.england.nhs.uk/digitaltechnology/nhs-federated-data-platform/security-privacy/nhs-fdp-privacy-notice", "retrieval_tags": [ "data-governance", "fdp", "governance", "health-data", "nhs", "palantir", "personal-data", "privacy-notice" ] } ] }, { "concept": "access_control_policy", "chunk_count": 7, "direct_source_count": 2, "top_sources": [ { "id": "phase16-oasis-xacml-3-policy-access-control-2013", "title": "eXtensible Access Control Markup Language (XACML) Version 3.0", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://docs.oasis-open.org/xacml/3.0/xacml-3.0-core-spec-os-en.html", "retrieval_tags": [ "access-control", "attribute-based-access-control", "governed-action", "oasis", "ontology-governance", "phase16", "policy-enforcement", "runtime-governance", "xacml" ] }, { "id": "phase11-joshi-2026-deontic-policies-agentic-ai-runtime-governance", "title": "Deontic Policies for Runtime Governance of Agentic AI Systems", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "candidate", "year": 2026, "url": "https://arxiv.org/abs/2606.19464", "retrieval_tags": [ "agentic-ai", "deontic-policy", "governed-action", "llm", "ontology-governance", "owl", "phase11", "policy-reasoning", "runtime-governance", "tool-use" ] } ] }, { "concept": "decentralized_linked_data", "chunk_count": 7, "direct_source_count": 2, "top_sources": [ { "id": "phase16-solid-protocol-linked-data-pods-2025", "title": "Solid Protocol", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://solidproject.org/TR/protocol", "retrieval_tags": [ "access-control", "decentralized-data", "federated-data-sharing", "linked-data", "ontology-governance", "phase16", "solid", "solid-pods" ] }, { "id": "p2-llm-ont-032", "title": "Data Catalog Vocabulary (DCAT) - Version 3", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "candidate", "year": 2024, "url": "https://www.w3.org/TR/vocab-dcat-3", "retrieval_tags": [ "data-catalog", "data-products", "dcat", "metadata", "rdf", "semantic-layer", "w3c" ] } ] }, { "concept": "palantir_ontology", "chunk_count": 690, "direct_source_count": 128, "top_sources": [ { "id": "phase2-pal-aip-observability-overview-2026", "title": "AIP observability: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-observability/overview", "retrieval_tags": [ "aip-observability", "core", "governance", "logs", "metrics", "palantir", "tracing", "workflow-lineage" ] }, { "id": "phase2-pal-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluate Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "core", "custom-evaluation", "governed-action", "ontology-edits", "palantir", "simulation", "validation", "write-capable-agents" ] }, { "id": "core-palantir-ontology-overview-2026", "title": "Ontology building: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology/overview", "retrieval_tags": [ "actions", "core", "digital-twin", "foundry", "kinetic-elements", "ontology", "operational-layer", "palantir", "semantic-elements" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "phase2-pal-ontology-mcp-overview-2026", "title": "Ontology MCP (OMCP) overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/ontology-mcp/overview", "retrieval_tags": [ "action-type", "agents", "core", "mcp", "object-type", "ontology-mcp", "palantir", "tool-use" ] }, { "id": "pal-doc-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluation functions and Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "governance", "ontology-edits", "palantir", "simulation", "testing" ] }, { "id": "pal-doc-aip-observability-2026", "title": "AIP observability", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/aip/aip-observability", "retrieval_tags": [ "aip-observability", "governance", "logs", "metrics", "palantir", "tracing" ] }, { "id": "pal-sec-2025-10k-2026", "title": "Palantir Technologies Inc. Form 10-K for fiscal year ended December 31, 2025", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://www.sec.gov/Archives/edgar/data/1321655/000132165526000011/pltr-20251231.htm", "retrieval_tags": [ "10-k", "aip", "foundry", "investor", "ontology", "palantir", "revenue", "risk-factors", "sec" ] } ] }, { "concept": "palantir_aip", "chunk_count": 224, "direct_source_count": 32, "top_sources": [ { "id": "phase2-pal-aip-observability-overview-2026", "title": "AIP observability: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-observability/overview", "retrieval_tags": [ "aip-observability", "core", "governance", "logs", "metrics", "palantir", "tracing", "workflow-lineage" ] }, { "id": "phase2-pal-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluate Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "core", "custom-evaluation", "governed-action", "ontology-edits", "palantir", "simulation", "validation", "write-capable-agents" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "pal-doc-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluation functions and Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "governance", "ontology-edits", "palantir", "simulation", "testing" ] }, { "id": "pal-doc-aip-observability-2026", "title": "AIP observability", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/aip/aip-observability", "retrieval_tags": [ "aip-observability", "governance", "logs", "metrics", "palantir", "tracing" ] }, { "id": "pal-sec-2025-10k-2026", "title": "Palantir Technologies Inc. Form 10-K for fiscal year ended December 31, 2025", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://www.sec.gov/Archives/edgar/data/1321655/000132165526000011/pltr-20251231.htm", "retrieval_tags": [ "10-k", "aip", "foundry", "investor", "ontology", "palantir", "revenue", "risk-factors", "sec" ] }, { "id": "pal-doc-aip-ethics-governance-2026", "title": "AI ethics and governance", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/ethics-governance", "retrieval_tags": [ "ai-governance", "aip-evals", "aip-logic", "data-health", "debugging", "evals", "interpretable-tools", "palantir", "responsible-ai" ] }, { "id": "phase3-pal-service-logs-debugging-2026", "title": "AIP observability: Service logs and debugging", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-observability/service-logs-and-debugging", "retrieval_tags": [ "aip-observability", "debugging", "logs", "palantir", "permissions", "privacy" ] } ] }, { "concept": "governed_action", "chunk_count": 873, "direct_source_count": 182, "top_sources": [ { "id": "phase2-pal-aip-observability-overview-2026", "title": "AIP observability: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-observability/overview", "retrieval_tags": [ "aip-observability", "core", "governance", "logs", "metrics", "palantir", "tracing", "workflow-lineage" ] }, { "id": "phase2-pal-aip-evals-ontology-edits-2026", "title": "AIP Evals: Evaluate Ontology edits", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-evals/ontology-edits", "retrieval_tags": [ "aip-evals", "core", "custom-evaluation", "governed-action", "ontology-edits", "palantir", "simulation", "validation", "write-capable-agents" ] }, { "id": "core-palantir-ontology-overview-2026", "title": "Ontology building: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology/overview", "retrieval_tags": [ "actions", "core", "digital-twin", "foundry", "kinetic-elements", "ontology", "operational-layer", "palantir", "semantic-elements" ] }, { "id": "oa-https-doi-org-10-1145-3447772", "title": "Knowledge Graphs", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "core", "year": 2021, "url": "https://dl.acm.org/doi/10.1145/3447772", "retrieval_tags": [ "ai", "commercial", "construction", "core", "data-integration", "embeddings", "knowledge-graph", "knowledge-graphs", "openalex", "rdf", "reasoning", "semantic-web" ] }, { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "w3c_shacl_2017", "title": "Shapes Constraint Language (SHACL)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2017, "url": "https://www.w3.org/TR/shacl", "retrieval_tags": [ "constraints", "core", "data-quality", "ontology-governance", "rdf", "semantic-governance", "semantic-web", "shacl", "validation", "w3c" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "phase2-nist-ai-rmf-1-0-2023", "title": "Artificial Intelligence Risk Management Framework (AI RMF 1.0)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2023, "url": "https://www.nist.gov/itl/ai-risk-management-framework", "retrieval_tags": [ "ai-risk-management", "core", "evaluation", "governance", "nist", "policy", "trustworthy-ai" ] } ] }, { "concept": "mcp", "chunk_count": 189, "direct_source_count": 47, "top_sources": [ { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "phase2-pal-ontology-mcp-overview-2026", "title": "Ontology MCP (OMCP) overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/ontology-mcp/overview", "retrieval_tags": [ "action-type", "agents", "core", "mcp", "object-type", "ontology-mcp", "palantir", "tool-use" ] }, { "id": "core-staab-studer-2009-handbook-ontologies", "title": "Handbook on Ontologies", "bucket": "books", "quality_signal": "widely_cited", "triage_tier": "core", "year": 2009, "url": "https://doi.org/10.1007/978-3-540-92673-3", "retrieval_tags": [ "book", "core", "handbook", "mapping", "matching", "ontology-engineering", "ontology-learning", "reasoning", "semantic-web" ] }, { "id": "phase2-mcp-spec-2025", "title": "Model Context Protocol Specification", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://modelcontextprotocol.io/specification/2025-06-18", "retrieval_tags": [ "agents", "context-protocol", "core", "interoperability", "mcp", "ontology-mcp", "semantic-layer", "tool-use" ] }, { "id": "pal-doc-aip-ethics-governance-2026", "title": "AI ethics and governance", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/ethics-governance", "retrieval_tags": [ "ai-governance", "aip-evals", "aip-logic", "data-health", "debugging", "evals", "interpretable-tools", "palantir", "responsible-ai" ] }, { "id": "phase4-palantir-logic-tools-rag-oag-2024", "title": "Building with Palantir AIP: Logic Tools for RAG/OAG", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://blog.palantir.com/building-with-palantir-aip-logic-tools-for-rag-oag-fdaf8938d02e", "retrieval_tags": [ "aip", "logic-tools", "oag", "ontology", "palantir", "rag" ] }, { "id": "pal-doc-data-security-overview-2026", "title": "Data security overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/security/data-security-overview", "retrieval_tags": [ "data-security", "foundry-security", "governance", "palantir", "permissions" ] }, { "id": "phase5-palantir-foundry-platform-summary-llm-2026", "title": "Foundry platform summary for LLMs", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/getting-started/foundry-platform-summary-llm", "retrieval_tags": [ "claude", "copilot-studio", "external-agents", "foundry", "gemini-enterprise", "llm", "mcp-hub", "oauth", "ontology-mcp", "palantir", "permissions", "phase5" ] } ] }, { "concept": "mcp_hub", "chunk_count": 9, "direct_source_count": 4, "top_sources": [ { "id": "phase5-palantir-foundry-platform-summary-llm-2026", "title": "Foundry platform summary for LLMs", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/getting-started/foundry-platform-summary-llm", "retrieval_tags": [ "claude", "copilot-studio", "external-agents", "foundry", "gemini-enterprise", "llm", "mcp-hub", "oauth", "ontology-mcp", "palantir", "permissions", "phase5" ] }, { "id": "phase5-palantir-mcp-hub-announcement-2026", "title": "Discover and manage Ontology MCP servers in MCP Hub", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/announcements/2026-05", "retrieval_tags": [ "data-governance", "external-agents", "mcp", "mcp-hub", "ontology-mcp", "palantir", "permissions", "phase5", "security", "tool-use" ] }, { "id": "phase5-palantir-ontology-mcp-getting-started-2026", "title": "Ontology MCP: Getting started", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology-mcp/getting-started", "retrieval_tags": [ "agent-configuration", "developer-console", "external-agents", "mcp-hub", "ontology-mcp", "palantir", "phase5", "tool-use" ] }, { "id": "phase2-anthropic-mcp-2024", "title": "Introducing the Model Context Protocol", "bucket": "technical", "quality_signal": "primary_source", "triage_tier": "candidate", "year": 2024, "url": "https://www.anthropic.com/news/model-context-protocol", "retrieval_tags": [ "agents", "anthropic", "context", "interoperability", "mcp", "tool-use" ] } ] }, { "concept": "semantic_layer", "chunk_count": 23, "direct_source_count": 3, "top_sources": [ { "id": "phase3-llm-ontmem-011", "title": "Schema Matching with Large Language Models: An Experimental Study", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2024, "url": "https://arxiv.org/abs/2407.11852", "retrieval_tags": [ "data-integration", "llm", "schema-matching", "semantic-alignment", "vldbw-2024" ] }, { "id": "phase3-llm-ontmem-024", "title": "Semantic Layers for Reliable LLM-Powered Data Analytics", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "low_priority", "year": 2026, "url": "https://arxiv.org/abs/2604.25149", "retrieval_tags": [ "business-metrics", "enterprise-ai", "governance", "llm-analytics", "reliability", "semantic-layer", "text-to-sql" ] }, { "id": "phase3-llm-ontmem-025", "title": "ConStruM: A Structure-Guided LLM Framework for Context-Aware Schema Matching", "bucket": "academic", "quality_signal": "preprint", "triage_tier": "low_priority", "year": 2026, "url": "https://arxiv.org/abs/2601.20482", "retrieval_tags": [ "context-aware", "llm", "schema-matching", "semantic-layer", "structure-guided" ] } ] }, { "concept": "data_product", "chunk_count": 16, "direct_source_count": 4, "top_sources": [ { "id": "industry-commercial-eccenca-corporate-memory", "title": "eccenca Corporate Memory knowledge graph and data product governance materials", "bucket": "commercial", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://eccenca.com/products/corporate-memory", "retrieval_tags": [ "ai-ready-kg", "corporate-memory", "data-products", "eccenca", "semantic-governance", "shacl" ] }, { "id": "phase14-fair-data-point-metadata-publication-2023", "title": "FAIR Data Point: A FAIR-Oriented Approach for Metadata Publication", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2023, "url": "https://doi.org/10.1162/dint_a_00160", "retrieval_tags": [ "dcat", "fair-data", "fair-data-point", "linked-data", "machine-actionable-metadata", "metadata-service", "phase14", "semantic-interoperability" ] }, { "id": "phase6-odps-41-open-data-product-specification", "title": "Open Data Product Specification 4.1", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "candidate", "year": 2026, "url": "https://opendataproducts.org/v4.1", "retrieval_tags": [ "data-mesh", "data-product", "governance", "metadata-model", "odps", "phase6" ] }, { "id": "p2-llm-ont-032", "title": "Data Catalog Vocabulary (DCAT) - Version 3", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "candidate", "year": 2024, "url": "https://www.w3.org/TR/vocab-dcat-3", "retrieval_tags": [ "data-catalog", "data-products", "dcat", "metadata", "rdf", "semantic-layer", "w3c" ] } ] }, { "concept": "data_contract", "chunk_count": 5, "direct_source_count": 1, "top_sources": [ { "id": "phase6-odcs-310-open-data-contract-standard", "title": "Open Data Contract Standard v3.1.0", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "candidate", "year": 2026, "url": "https://bitol-io.github.io/open-data-contract-standard/v3.1.0", "retrieval_tags": [ "data-contract", "data-governance", "odcs", "phase6", "producer-consumer", "quality-rules", "schema", "validation" ] } ] }, { "concept": "data_lineage", "chunk_count": 4, "direct_source_count": 1, "top_sources": [ { "id": "phase6-openlineage-docs-specification", "title": "OpenLineage Documentation and Specification", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "candidate", "year": 2026, "url": "https://openlineage.io/docs", "retrieval_tags": [ "data-lineage", "facets", "metadata-events", "openlineage", "phase6", "pipeline-observability", "provenance" ] } ] }, { "concept": "digital_twin", "chunk_count": 69, "direct_source_count": 20, "top_sources": [ { "id": "core-palantir-ontology-overview-2026", "title": "Ontology building: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology/overview", "retrieval_tags": [ "actions", "core", "digital-twin", "foundry", "kinetic-elements", "ontology", "operational-layer", "palantir", "semantic-elements" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "pal-doc-platform-overview-2026", "title": "Platform overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/platform-overview/overview", "retrieval_tags": [ "ai-mesh", "aip", "apollo", "foundry", "ontology-layer", "palantir", "platform-overview" ] }, { "id": "pal-doc-logic-overview-2026", "title": "AIP Logic: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/logic/overview", "retrieval_tags": [ "aip-logic", "human-review", "llm-tools", "logic-functions", "ontology", "ontology-edits", "palantir", "workflow", "workflows" ] }, { "id": "phase2-pal-ontology-mcp-auth-2026", "title": "Ontology MCP: Authentication and authorization", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/ontology-mcp/authentication-and-authorization", "retrieval_tags": [ "governed-action", "mcp", "oauth", "ontology-mcp", "palantir", "permissions", "security" ] }, { "id": "pal-doc-osdk-typescript-2026", "title": "Ontology SDK: TypeScript OSDK", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/ontology-sdk/typescript-osdk", "retrieval_tags": [ "actions", "functions", "ontology", "ontology-sdk", "osdk", "palantir", "queries", "typed-client", "typescript", "typescript-osdk" ] }, { "id": "pal-doc-why-ontology-2026", "title": "Why create an Ontology?", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology/why-ontology", "retrieval_tags": [ "agents", "data-logic-action-security", "decision-centric", "operations", "palantir" ] }, { "id": "phase3-pal-sec-10k-2024", "title": "Palantir Technologies Inc. 2024 Form 10-K", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2025, "url": "https://www.sec.gov/Archives/edgar/data/1321655/000132165525000022/pltr-20241231.htm", "retrieval_tags": [ "10-k", "aip", "enterprise-ai", "foundry", "gotham", "palantir", "sec" ] } ] }, { "concept": "industrial_semantic_standards", "chunk_count": 23, "direct_source_count": 8, "top_sources": [ { "id": "phase16-iec-common-data-dictionary-cdd", "title": "IEC Common Data Dictionary (IEC CDD)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2025, "url": "https://cdd.iec.ch", "retrieval_tags": [ "common-data-dictionary", "data-dictionary", "iec", "industrial-semantic-standards", "ontology-governance", "phase16", "product-classification", "semantic-interoperability" ] }, { "id": "phase16-eclass-rdf-owl-product-classification", "title": "eCl@ss in RDF/OWL", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2025, "url": "https://www.eclass.eu/en/standard/eclassrdfowl", "retrieval_tags": [ "eclass", "industrial-semantic-standards", "ontology-governance", "phase16", "product-classification", "rdf", "semantic-interoperability", "supply-chain" ] }, { "id": "phase15-idsa-semantic-interoperability-data-spaces-2024", "title": "Semantic Interoperability in Data Spaces", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "core", "year": 2024, "url": "https://zenodo.org/records/10964377", "retrieval_tags": [ "data-governance", "data-sovereignty", "data-space", "dataspaces", "idsa", "phase15", "semantic-interoperability", "usage-policy" ] }, { "id": "phase16-etsi-saref-smart-applications-reference-ontology", "title": "SAREF: Smart Applications REFerence Ontology", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "candidate", "year": 2025, "url": "https://saref.etsi.org", "retrieval_tags": [ "digital-twin", "industrial-semantic-standards", "iot", "measurements", "ontology-standard", "phase16", "saref", "semantic-interoperability", "smart-applications" ] }, { "id": "phase15-ids-information-model-ontology-2020", "title": "The International Data Spaces Information Model - An Ontology for Sovereign Exchange of Digital Content", "bucket": "academic", "quality_signal": "peer_reviewed", "triage_tier": "candidate", "year": 2020, "url": "https://doi.org/10.1007/978-3-030-62466-8_12", "retrieval_tags": [ "data-sovereignty", "data-space", "dataspaces", "ids-information-model", "ontology", "phase15", "semantic-interoperability", "usage-policy" ] }, { "id": "oa-https-doi-org-10-1016-j-autcon-2020-103179", "title": "Towards a semantic Construction Digital Twin: Directions for future research", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2020, "url": "https://doi.org/10.1016/j.autcon.2020.103179", "retrieval_tags": [ "bim", "construction", "dynamic-data", "foundational", "lifecycle", "ontology", "openalex", "semantic-digital-twin" ] }, { "id": "phase6-idta-aas-metamodel-01001", "title": "Specification of the Asset Administration Shell Part 1: Metamodel, IDTA Number 01001", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "candidate", "year": 2024, "url": "https://industrialdigitaltwin.org/en?specificationpapers=specification-of-the-asset-administration-shell-part-1-metamodel-idta-number-01001", "retrieval_tags": [ "aas", "asset-administration-shell", "digital-twin", "industry-4-0", "metamodel", "phase6" ] }, { "id": "phase16-opc-ua-address-space-model-10000-3", "title": "OPC Unified Architecture Part 3: Address Space Model", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "candidate", "year": 2025, "url": "https://reference.opcfoundation.org/Core/Part3", "retrieval_tags": [ "address-space-model", "digital-twin", "industrial-semantic-standards", "industry-4-0", "information-model", "opc-ua", "operational-objects", "phase16" ] } ] }, { "concept": "ontology_governance", "chunk_count": 647, "direct_source_count": 136, "top_sources": [ { "id": "phase2-pal-aip-observability-overview-2026", "title": "AIP observability: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip-observability/overview", "retrieval_tags": [ "aip-observability", "core", "governance", "logs", "metrics", "palantir", "tracing", "workflow-lineage" ] }, { "id": "core-palantir-ontology-overview-2026", "title": "Ontology building: Overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/docs/foundry/ontology/overview", "retrieval_tags": [ "actions", "core", "digital-twin", "foundry", "kinetic-elements", "ontology", "operational-layer", "palantir", "semantic-elements" ] }, { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "w3c_shacl_2017", "title": "Shapes Constraint Language (SHACL)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2017, "url": "https://www.w3.org/TR/shacl", "retrieval_tags": [ "constraints", "core", "data-quality", "ontology-governance", "rdf", "semantic-governance", "semantic-web", "shacl", "validation", "w3c" ] }, { "id": "core-palantir-aip-overview-2026", "title": "AIP overview", "bucket": "palantir", "quality_signal": "official_docs", "triage_tier": "core", "year": 2026, "url": "https://palantir.com/docs/foundry/aip/overview", "retrieval_tags": [ "agents", "ai-platform", "aip", "aip-evals", "aip-logic", "automation", "core", "generative-ai", "llm", "ontology", "operations", "palantir" ] }, { "id": "phase2-nist-ai-rmf-1-0-2023", "title": "Artificial Intelligence Risk Management Framework (AI RMF 1.0)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2023, "url": "https://www.nist.gov/itl/ai-risk-management-framework", "retrieval_tags": [ "ai-risk-management", "core", "evaluation", "governance", "nist", "policy", "trustworthy-ai" ] }, { "id": "phase2-eu-ai-act-2024", "title": "Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj", "retrieval_tags": [ "core", "eu-ai-act", "governance", "human-oversight", "logging", "public-sector", "regulation", "risk-management" ] }, { "id": "phase2-iso-iec-42001-2023", "title": "ISO/IEC 42001:2023 Artificial intelligence - Management system", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2023, "url": "https://www.iso.org/standard/81230.html", "retrieval_tags": [ "ai-management-system", "core", "governance", "iso", "lifecycle", "policy", "risk-management" ] } ] }, { "concept": "ai_governance", "chunk_count": 83, "direct_source_count": 27, "top_sources": [ { "id": "phase2-nist-genai-profile-2024", "title": "Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf", "retrieval_tags": [ "core", "evaluation", "generative-ai", "governance", "hallucination", "nist", "privacy", "risk" ] }, { "id": "phase2-nist-ai-rmf-1-0-2023", "title": "Artificial Intelligence Risk Management Framework (AI RMF 1.0)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2023, "url": "https://www.nist.gov/itl/ai-risk-management-framework", "retrieval_tags": [ "ai-risk-management", "core", "evaluation", "governance", "nist", "policy", "trustworthy-ai" ] }, { "id": "phase2-eu-ai-act-2024", "title": "Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj", "retrieval_tags": [ "core", "eu-ai-act", "governance", "human-oversight", "logging", "public-sector", "regulation", "risk-management" ] }, { "id": "phase16-oasis-xacml-3-policy-access-control-2013", "title": "eXtensible Access Control Markup Language (XACML) Version 3.0", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2013, "url": "https://docs.oasis-open.org/xacml/3.0/xacml-3.0-core-spec-os-en.html", "retrieval_tags": [ "access-control", "attribute-based-access-control", "governed-action", "oasis", "ontology-governance", "phase16", "policy-enforcement", "runtime-governance", "xacml" ] }, { "id": "phase3-timmermans-epstein-2010-sociology-standards", "title": "A World of Standards but Not a Standard World: Toward a Sociology of Standards and Standardization", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 2010, "url": "https://doi.org/10.1146/annurev.soc.012809.102629", "retrieval_tags": [ "coordination", "local-practice", "phase3", "sociology", "standardization", "standards" ] }, { "id": "phase3-khatri-brown-2010-data-governance", "title": "Designing Data Governance", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 2010, "url": "https://doi.org/10.1145/1629175.1629210", "retrieval_tags": [ "accountability", "data-governance", "data-quality", "decision-rights", "metadata", "phase3" ] }, { "id": "phase4-std-eu-hleg-trustworthy-ai-guidelines-2019", "title": "Ethics Guidelines for Trustworthy AI", "bucket": "technical", "quality_signal": "official_docs", "triage_tier": "candidate", "year": 2019, "url": "https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai", "retrieval_tags": [ "accountability", "ethics", "eu", "governance", "human-oversight", "transparency", "trustworthy-ai" ] }, { "id": "oa-https-doi-org-10-1007-s00146-019-00932-9", "title": "Algorithms and values in justice and security", "bucket": "palantir", "quality_signal": "scholarly_index", "triage_tier": "candidate", "year": 2020, "url": "https://openalex.org/W2999513617", "retrieval_tags": [ "openalex", "palantir" ] } ] }, { "concept": "public_sector_ai", "chunk_count": 190, "direct_source_count": 39, "top_sources": [ { "id": "phase2-eu-ai-act-2024", "title": "Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act)", "bucket": "technical", "quality_signal": "official_standard", "triage_tier": "core", "year": 2024, "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/oj", "retrieval_tags": [ "core", "eu-ai-act", "governance", "human-oversight", "logging", "public-sector", "regulation", "risk-management" ] }, { "id": "pal-pcl-2026", "title": "Privacy and Civil Liberties", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://www.palantir.com/pcl", "retrieval_tags": [ "civil-liberties", "governance", "palantir", "privacy", "public-sector", "public-trust" ] }, { "id": "phase6-nhs-ndit-fdp-dpia-2026", "title": "FDP Data Protection Impact Assessment: NDIT Identifiable Version v3.0", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "core", "year": 2026, "url": "https://www.england.nhs.uk/wp-content/uploads/2025/08/redacted-ndit-nhs-england-fdp-dpia-identifiable-version-v3.0.pdf", "retrieval_tags": [ "data-protection", "dpia", "fdp", "identifiable-data", "ndit", "nhs", "ontology-definition", "palantir", "phase6", "privacy" ] }, { "id": "nhs-fdp-privacy-notice-2024", "title": "NHS Federated Data Platform privacy notice", "bucket": "technical", "quality_signal": "primary_source", "triage_tier": "core", "year": 2024, "url": "https://www.england.nhs.uk/digitaltechnology/nhs-federated-data-platform/security-privacy/nhs-fdp-privacy-notice", "retrieval_tags": [ "data-governance", "fdp", "governance", "health-data", "nhs", "palantir", "personal-data", "privacy-notice" ] }, { "id": "phase4-palantir-fdp-evaluation-partner-tender-2026", "title": "Federated Data Platform (FDP) - Evaluation Partner", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "candidate", "year": 2026, "url": "https://www.find-tender.service.gov.uk/procurement/ocds-h6vhtk-05ec4c", "retrieval_tags": [ "evaluation", "fdp", "governance", "nhs", "palantir", "procurement" ] }, { "id": "phase4-palantir-nhs-fdp-ig-cyber-2023", "title": "NHS Federated Data Platform and Associated Services Document 2: Information Governance and Cyber Security", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "candidate", "year": 2023, "url": "https://atamis-1928.my.salesforce-sites.com/servlet/servlet.FileDownload?file=00P8d000009dbdlEAA", "retrieval_tags": [ "cybersecurity", "fdp", "information-governance", "nhs", "palantir", "procurement" ] }, { "id": "phase4-palantir-hansard-fdp-contract-award-2023", "title": "NHS Federated Data Platform: Contract Award", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "candidate", "year": 2023, "url": "https://hansard.parliament.uk/commons/2023-11-21/debates/23112160000011/NHSFederatedDataPlatformContractAward", "retrieval_tags": [ "fdp", "governance", "nhs", "palantir", "parliament", "procurement" ] }, { "id": "phase4-palantir-sec-proxy-2026", "title": "Palantir Technologies Inc. 2026 Proxy Statement", "bucket": "palantir", "quality_signal": "primary_source", "triage_tier": "candidate", "year": 2026, "url": "https://www.sec.gov/Archives/edgar/data/1321655/000132165526000019/pltr-20260423.htm", "retrieval_tags": [ "governance", "investor-disclosure", "palantir", "proxy", "sec" ] } ] }, { "concept": "sociotechnical_systems", "chunk_count": 71, "direct_source_count": 13, "top_sources": [ { "id": "oa-https-doi-org-10-36227-techrxiv-175624549-98427022-v1", "title": "Enterprise Digital Twins in Financial Services: Convergence of Architecture, Operations, and Engineering", "bucket": "palantir", "quality_signal": "scholarly_index", "triage_tier": "core", "year": 2025, "url": "https://openalex.org/W4413638561", "retrieval_tags": [ "openalex", "palantir" ] }, { "id": "phase3-selbst-etal-2019-fairness-abstraction", "title": "Fairness and Abstraction in Sociotechnical Systems", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 2019, "url": "https://doi.org/10.1145/3287560.3287598", "retrieval_tags": [ "abstraction-trap", "ai-governance", "critique", "fairness", "phase3", "sociotechnical-systems" ] }, { "id": "phase3-trist-bamforth-1951-sociotechnical-systems", "title": "Some Social and Psychological Consequences of the Longwall Method of Coal-Getting", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1951, "url": "https://doi.org/10.1177/001872675100400101", "retrieval_tags": [ "critique", "human-factors", "organization", "phase3", "sociotechnical-systems", "work-design" ] }, { "id": "phase3-star-ruhleder-1996-ecology-infrastructure", "title": "Steps Toward an Ecology of Infrastructure: Design and Access for Large Information Spaces", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1996, "url": "https://doi.org/10.1287/isre.7.1.111", "retrieval_tags": [ "access", "adoption", "information-infrastructure", "organizational-practice", "phase3", "sociotechnical" ] }, { "id": "oa-https-doi-org-10-1016-j-autcon-2020-103179", "title": "Towards a semantic Construction Digital Twin: Directions for future research", "bucket": "academic", "quality_signal": "peer_reviewed_survey", "triage_tier": "candidate", "year": 2020, "url": "https://doi.org/10.1016/j.autcon.2020.103179", "retrieval_tags": [ "bim", "construction", "dynamic-data", "foundational", "lifecycle", "ontology", "openalex", "semantic-digital-twin" ] }, { "id": "phase3-emery-trist-1960-sociotechnical-systems", "title": "Socio-Technical Systems", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1960, "url": "https://books.google.com/books?id=GoNQAAAAMAAJ", "retrieval_tags": [ "ai-deployment", "joint-optimization", "organization-design", "phase3", "sociotechnical-theory" ] }, { "id": "phase3-orlikowski-gash-1994-technological-frames", "title": "Technological Frames: Making Sense of Information Technology in Organizations", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1994, "url": "https://doi.org/10.1145/192844.193034", "retrieval_tags": [ "adoption", "interpretation", "organizational-change", "phase3", "stakeholders", "technological-frames" ] }, { "id": "phase3-orlikowski-1992-duality-technology", "title": "The Duality of Technology: Rethinking the Concept of Technology in Organizations", "bucket": "academic", "quality_signal": "widely_cited", "triage_tier": "candidate", "year": 1992, "url": "https://doi.org/10.1287/orsc.3.3.398", "retrieval_tags": [ "enactment", "organization-theory", "phase3", "sociotechnical", "technology-in-practice" ] } ] } ], "synthesis_routes": [ { "id": "ontology_foundations", "title": "Ontology foundations: explicit commitments, not taxonomies", "retrieval_concepts": [ "ontology", "formal_ontology", "knowledge_representation", "ontology_engineering", "validation" ], "source_ids": [ "core-gruber-1993-portable-ontology", "oa-https-doi-org-10-1006-ijhc-1995-1081", "core-guarino-1998-formal-ontology-information-systems", "guarino_oberle_staab_2009_what_is_ontology", "core-noy-mcguinness-2001-ontology-101", "core-baader-2003-description-logic-handbook", "core-bfo-iso-21838-2" ], "caveats": [ "Do not imply every enterprise ontology is a complete formal ontology.", "Distinguish ontology, taxonomy, controlled vocabulary, schema, and graph database." ] }, { "id": "standards_stack", "title": "Standards stack: from graph data to validation and governance", "retrieval_concepts": [ "semantic_web", "semantic_schema", "ontology_mapping_metadata", "mapping_language", "machine_actionable_metadata", "validation", "provenance", "data_quality", "usage_policy", "data_product" ], "source_ids": [ "core-w3c-rdf-11-concepts", "core-w3c-owl2-overview", "core-w3c-sparql-11-query", "w3c_shacl_2017", "w3c_skos_reference_2009", "phase2-w3c-prov-o-2013", "p2-llm-ont-032", "phase14-schemaorg-evolution-structured-data-web-2016", "phase14-linkml-open-data-modeling-framework-2026", "phase14-sssom-ontological-mappings-2022", "phase4-std-w3c-r2rml-2012", "phase15-w3c-direct-mapping-relational-data-rdf-2012", "phase15-dimou-2014-rml-integrated-rdf-mappings", "phase15-rml-specification-heterogeneous-rdf-mapping-2024", "phase15-yarrrml-human-readable-rdf-generation-rules-2025", "phase4-std-w3c-odrl-model-2018", "phase4-std-w3c-dqv-2016", "p2-llm-ont-036", "phase14-fair-data-point-metadata-publication-2023", "phase14-fair-digital-object-conceptual-model-2023", "phase16-w3c-sparql11-federated-query-2013", "phase6-odcs-310-open-data-contract-standard", "phase6-odps-41-open-data-product-specification", "phase6-openlineage-docs-specification", "phase6-omg-dmn-15", "phase4-std-dpv-2-0-2024", "phase16-oasis-xacml-3-policy-access-control-2013" ], "caveats": [ "Standards show mechanisms, not automatic adoption or successful governance.", "OWL reasoning, SHACL validation, and policy enforcement are different layers and should not be collapsed." ] }, { "id": "ontology_evaluation_lifecycle", "title": "Ontology evaluation and lifecycle governance: quality before action", "retrieval_concepts": [ "ontology_quality", "ontology_evaluation", "ontology_evolution", "ontology_reporting", "ontology_governance", "validation" ], "source_ids": [ "fernandez_lopez_gomez_perez_juristo_1997_methontology", "guarino_welty_2002_ontoclean", "phase2-poveda-2014-oops", "suarez_figueroa_2015_neon", "phase16-noy-klein-2004-ontology-evolution-schema-evolution", "phase16-miro-guidelines-minimum-information-reporting-ontology-2017", "phase16-fairsharing-community-standards-repositories-policies-2019", "phase7-ontology-development-kit-toolkit-2022", "phase7-robot-automating-ontology-workflows-2019", "phase6-lippolis-2025-llm-assisting-ontology-evaluation", "phase6-kampars-2025-llm-collaborative-ontology-design" ], "caveats": [ "Automated pitfall scanners and reporting checklists improve governance but do not replace domain expert review.", "Ontology versioning and migration are operational programs, not one-time modeling decisions." ] }, { "id": "scientific_ontology_infrastructure", "title": "Scientific ontology infrastructure: community knowledge as machine substrate", "retrieval_concepts": [ "scientific_ontology_infrastructure", "gene_ontology", "biomedical_ontology", "ontology_workflow", "ontology_identifier_governance", "curated_knowledge_infrastructure", "ontology_aware_ai", "ai_for_science" ], "source_ids": [ "core-gene-ontology-2000", "phase7-gene-ontology-knowledgebase-2023", "phase7-go-cam-causal-activity-modeling-2019", "smith_etal_2007_obo_foundry", "phase7-obo-foundry-2021-operationalizing-open-data-principles", "phase7-ontology-development-kit-toolkit-2022", "phase7-robot-automating-ontology-workflows-2019", "noy_etal_2009_bioportal", "phase7-ols4-ontology-lookup-service-2025", "phase7-ontobee-linked-ontology-server-2016", "phase7-bioregistry-biomedical-entity-identification-2022", "wilkinson_etal_2016_fair", "phase7-ro-crate-packaging-research-artefacts-2022", "phase7-human-phenotype-ontology-2024", "phase7-monarch-initiative-2024", "phase7-edam-bioinformatics-ontology-2013", "phase7-deepgo-se-semantic-entailment-2024" ], "caveats": [ "Biomedical ontology success depends on years of community curation; it should not be presented as something LLMs can cheaply reproduce.", "Scientific ontology infrastructure proves the value of shared semantics, but not that every enterprise ontology has the same openness or accountability." ] }, { "id": "llm_kg_rag", "title": "LLM + KG + RAG: external semantic memory for generative systems", "retrieval_concepts": [ "llm_kg", "knowledge_graph", "rag", "ontology_grounded_rag", "hallucination_mitigation", "graphrag", "memgraphrag", "kgqa" ], "source_ids": [ "arxiv-2306-08302v3", "oa-https-doi-org-10-1145-3447772", "oa-https-doi-org-10-1109-tnnls-2021-3070843", "core-lewis-2020-rag", "core-edge-2024-graphrag", "phase6-sharma-2025-og-rag", "phase6-oarga-2026-scientific-kg-ontology-open-llms", "phase6-zhou-2025-kg-rag-incompleteness", "phase6-xiang-2025-when-to-use-graphs-rag", "phase11-ali-2026-ontology-grounded-kg-clinical-hallucinations", "phase11-wu-2026-memgraphrag-memory-multi-agent-graphrag", "ont-ai-024", "ont-ai-022", "ont-ai-023", "phase2-gutierrez-2025-hipporag2", "phase5-liu-2025-ontology-guided-reverse-thinking-kgqa", "phase6-sui-2025-fidelis-kgqa" ], "caveats": [ "Generated graphs are only as good as extraction, entity resolution, summarization, and provenance.", "Preprints such as KAG, LightRAG, and HippoRAG variants are architecture evidence; avoid treating them as settled field consensus." ] }, { "id": "ontology_engineering_llms", "title": "LLMs as ontology engineering assistants", "retrieval_concepts": [ "ontology_learning", "ontology_matching", "ontology_engineering", "enterprise_ontology_construction", "ontology_evaluation", "schema_alignment", "llm" ], "source_ids": [ "phase2-li-garijo-poveda-2025-llm-oe-review", "ont-ai-004", "p2-llm-ont-006", "phase3-llm-ontmem-023", "phase2-llms4om-2024", "phase2-agent-om-2023", "p2-llm-ont-007", "p2-llm-ont-030", "phase6-lippolis-2025-llm-assisting-ontology-evaluation", "phase6-zhao-2025-llm-ontology-requirements-engineering", "phase6-lippolis-2025-domain-specific-ontology-generation-llms", "phase6-kampars-2025-llm-collaborative-ontology-design", "phase11-oyewale-soru-2026-ontoekg-enterprise-ontology-construction", "phase11-soares-wassermann-2026-specific-domain-ontology-construction-llms", "p2-llm-ont-006" ], "caveats": [ "Many LLM ontology engineering studies are preprints or early benchmarks.", "High extraction scores do not guarantee maintainable ontology design." ] }, { "id": "palantir_operational_ontology", "title": "Palantir: ontology as executable operational layer", "retrieval_concepts": [ "palantir_ontology", "palantir_aip", "governed_action", "mcp", "mcp_hub", "decision_lineage", "ontology_governance" ], "source_ids": [ "core-palantir-ontology-overview-2026", "core-palantir-aip-overview-2026", "phase2-pal-ontology-mcp-overview-2026", "phase2-pal-aip-evals-ontology-edits-2026", "phase2-pal-aip-observability-overview-2026", "pal-doc-aip-ethics-governance-2026", "phase3-pal-mcp-installation-2026", "phase3-pal-mcp-security-2026", "phase5-palantir-connecting-agents-decisions-2026", "phase5-palantir-mcp-hub-announcement-2026", "phase5-palantir-foundry-platform-summary-llm-2026" ], "caveats": [ "Most architecture evidence is official/vendor-authored; label it as Palantir documentation, not independent validation.", "Controls demonstrate design, not necessarily real-world safety, fairness, or public legitimacy.", "Commercial ROI and customer-impact claims must stay separate from technical architecture evidence." ] }, { "id": "enterprise_comparators", "title": "Enterprise comparators: semantic layers, data products, digital twins, and agent memory", "retrieval_concepts": [ "semantic_layer", "ontology_based_data_access", "virtual_knowledge_graph", "knowledge_graph_construction_pipeline", "data_space", "federated_data_sharing", "industrial_semantic_standards", "compliance_policy_reasoning", "ml_dataset_metadata", "open_knowledge_graph", "data_product", "agent_memory", "temporal_knowledge_graph", "digital_twin", "brick_schema", "ontology_grounding" ], "source_ids": [ "phase3-llm-ontmem-024", "p2-llm-ont-029", "phase4-enterprise-databricks-genie-semantic-model-2026", "phase4-enterprise-google-looker-semantic-model-gemini-2026", "phase4-enterprise-microsoft-fabric-semantic-model-copilot-2026", "phase4-enterprise-dataworld-ai-context-engine-2026", "phase4-enterprise-dbt-semantic-layer-2026", "phase14-xiao-2018-ontology-based-data-access-survey", "phase14-calvanese-2016-ontop-answering-sparql-relational-databases", "phase15-arenas-2024-morph-kgc-scalable-kg-materialization", "phase14-croissant-ml-ready-dataset-metadata-2024", "phase14-wikidata-free-collaborative-knowledgebase-2014", "phase15-ids-information-model-ontology-2020", "phase15-idsa-semantic-interoperability-data-spaces-2024", "phase15-dataspace-protocol-2025-1", "phase15-gaiax-ontology-compliance-policy-reasoning-2023", "phase16-opc-ua-address-space-model-10000-3", "phase16-etsi-saref-smart-applications-reference-ontology", "phase16-eclass-rdf-owl-product-classification", "phase16-iec-common-data-dictionary-cdd", "phase16-solid-protocol-linked-data-pods-2025", "p2-llm-ont-036", "phase6-odcs-310-open-data-contract-standard", "phase6-odps-41-open-data-product-specification", "phase6-openlineage-docs-specification", "phase6-idta-aas-metamodel-01001", "phase11-qian-2026-brick-dicl-schema-classification", "phase11-shuai-2026-usd-scenes-ontology-grounding-llms", "phase6-xu-2025-a-mem-agentic-memory", "phase3-llm-ontmem-018" ], "caveats": [ "Vendor documentation often lacks controlled measurement.", "Semantic layers can become stale unless ownership, versioning, validation, and change workflow are explicit." ] }, { "id": "governance_sociotechnical", "title": "Governance and sociotechnical critique", "retrieval_concepts": [ "sociotechnical_systems", "boundary_object", "classification_infrastructure", "contextual_integrity", "data_governance", "ai_governance" ], "source_ids": [ "phase3-star-griesemer-1989-boundary-objects", "phase3-bowker-star-1999-sorting-things-out", "phase3-star-ruhleder-1996-ecology-infrastructure", "phase3-nissenbaum-2010-privacy-context", "phase3-selbst-etal-2019-fairness-abstraction", "phase3-raji-etal-2020-accountability-gap", "phase2-nist-ai-rmf-1-0-2023", "phase2-nist-genai-profile-2024", "phase2-eu-ai-act-2024", "nhs-fdp-contract-explainer-2026", "phase6-nhs-fdp-contracts-finder-2024", "phase6-nhs-ndit-fdp-dpia-2026", "phase6-parliament-rewiring-state-2026", "phase6-ico-dhsc-fdp-foi-2026", "phase6-bmj-morley-zhang-fdp-2023", "phase6-digital-health-ndg-palantir-access-2026", "nhs-fdp-privacy-notice-2024", "bmj-palantir-nhs-contract-2023", "privacy-intl-all-roads-palantir-2021", "amnesty-palantir-human-rights-2020", "oa-https-doi-org-10-1080-01972243-2022-2100851" ], "caveats": [ "Critique sources should be labeled by type: civil-society report, opinion, journalism, academic article, or official record.", "Do not infer misconduct from the existence of public controversy; use it to frame governance and legitimacy questions." ] }, { "id": "research_agenda", "title": "Research agenda: from semantic models to accountable AI action", "retrieval_concepts": [ "ontology_constrained_reasoning", "runtime_governance", "predeployment_assurance", "semantic_schema", "ontology_mapping_metadata", "mapping_language", "machine_actionable_metadata", "data_space", "compliance_policy_reasoning", "privacy_vocabulary", "access_control_policy", "decentralized_linked_data", "curated_knowledge_infrastructure", "kgqa", "validation", "provenance", "ai_governance", "verifiable_credentials" ], "source_ids": [ "phase11-tuan-sanyal-2026-ontology-constrained-neural-reasoning-enterprise-agents", "phase5-liu-2025-ontology-guided-reverse-thinking-kgqa", "phase6-sharma-2025-og-rag", "phase6-xiang-2025-when-to-use-graphs-rag", "phase11-joshi-2026-deontic-policies-agentic-ai-runtime-governance", "phase11-tuan-sanyal-2026-predeployment-assurance-ontology-simulation", "phase11-tuan-sanyal-2026-ontology-constrained-neural-reasoning-enterprise-agents", "phase11-hamed-rocha-2026-biomedical-rag-majority-voting-verification-protocol", "phase3-llm-ontmem-018", "phase2-li-garijo-poveda-2025-llm-oe-review", "phase2-nist-genai-profile-2024", "w3c_shacl_2017", "phase2-w3c-prov-o-2013", "phase16-oasis-xacml-3-policy-access-control-2013", "phase4-std-dpv-2-0-2024", "phase16-w3c-sparql11-federated-query-2013", "phase6-odcs-310-open-data-contract-standard", "phase6-openlineage-docs-specification", "phase4-std-w3c-vc-data-model-2-2025", "phase14-linkml-open-data-modeling-framework-2026", "phase14-sssom-ontological-mappings-2022", "phase14-fair-data-point-metadata-publication-2023", "phase14-hoyt-gyori-2024-o3-guidelines-curated-resources", "phase15-dataspace-protocol-2025-1", "phase15-gaiax-ontology-compliance-policy-reasoning-2023" ], "caveats": [ "Keep frontier claims modest and distinguish architecture proposals from mature deployments.", "Nature-style argument should state uncertainty and open questions explicitly." ] }, { "id": "frontier_2026_evidence", "title": "2026 frontier evidence: ontology for hallucination control, graph memory, and agent governance", "retrieval_concepts": [ "hallucination_mitigation", "enterprise_ontology_construction", "memgraphrag", "runtime_governance", "predeployment_assurance", "domain_grounded_ai", "ontology_grounding", "brick_schema" ], "source_ids": [ "phase11-ali-2026-ontology-grounded-kg-clinical-hallucinations", "phase11-hamed-rocha-2026-biomedical-rag-majority-voting-verification-protocol", "phase11-oyewale-soru-2026-ontoekg-enterprise-ontology-construction", "phase11-soares-wassermann-2026-specific-domain-ontology-construction-llms", "phase11-wu-2026-memgraphrag-memory-multi-agent-graphrag", "phase11-joshi-2026-deontic-policies-agentic-ai-runtime-governance", "phase11-tuan-sanyal-2026-predeployment-assurance-ontology-simulation", "phase11-tuan-sanyal-2026-ontology-constrained-neural-reasoning-enterprise-agents", "phase11-qian-2026-brick-dicl-schema-classification", "phase11-shuai-2026-usd-scenes-ontology-grounding-llms" ], "caveats": [ "Most sources in this route are preprints; use them to show frontier direction, not settled consensus.", "Do not merge vendor claims and preprint claims into a single proof of deployment effectiveness.", "Biomedical DOI sources are stronger evidence for hallucination/verification themes than enterprise-agent preprints." ] } ] }