# Longform References

This reference list is generated from source-ID evidence anchors in `research/synthesis/longform_draft_zh.md`.

- Distinct source IDs: 99
- Total mentions: 109
- Missing source IDs: 0

## Bucket Summary

- academic: 64
- books: 3
- commercial: 5
- palantir: 13
- technical: 14

## References

1. Thanh Luong Tuan; Abhijit Sanyal (2026). Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agents. arXiv. [phase11-tuan-sanyal-2026-ontology-constrained-neural-reasoning-enterprise-agents](https://arxiv.org/abs/2604.00555) — academic; preprint; candidate; mentions: 2.
2. J. Li; D. Garijo; M. Poveda-Villalon (2025). Large Language Models for Ontology Engineering: A Systematic Literature Review. Semantic Web Journal preprint. [phase2-li-garijo-poveda-2025-llm-oe-review](https://www.semantic-web-journal.net/content/large-language-models-ontology-engineering-systematic-literature-review) — academic; peer_reviewed_survey; core; mentions: 2.
3. National Institute of Standards and Technology (2024). Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile. NIST. [phase2-nist-genai-profile-2024](https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf) — technical; official_standard; core; mentions: 2.
4. J. Kampars; G. Mosans; T. Jogi; F. Roters; N. Vajragupta (2025). LLM-Supported Collaborative Ontology Design for Data and Knowledge Management Platforms. Frontiers in Big Data. [phase6-kampars-2025-llm-collaborative-ontology-design](https://doi.org/10.3389/fdata.2025.1676477) — academic; peer_reviewed; low_priority; mentions: 2.
5. Anna Sofia Lippolis; Mohammad Javad Saeedizade; Robin Keskisarkka; Aldo Gangemi; Eva Blomqvist; Andrea Giovanni Nuzzolese (2025). Large Language Models Assisting Ontology Evaluation. ISWC 2025 / The Semantic Web. [phase6-lippolis-2025-llm-assisting-ontology-evaluation](https://doi.org/10.1007/978-3-032-09527-5_27) — academic; peer_reviewed; candidate; mentions: 2.
6. Kartik Sharma; Peeyush Kumar; Yunqing Li (2025). OG-RAG: Ontology-Grounded Retrieval-Augmented Generation for Large Language Models. EMNLP 2025 / ACL Anthology. [phase6-sharma-2025-og-rag](https://aclanthology.org/2025.emnlp-main.1674) — academic; peer_reviewed; candidate; mentions: 2.
7. Zhishang Xiang; Chuanjie Wu; Qinggang Zhang; Shengyuan Chen; Zijin Hong; Xiao Huang; Jinsong Su (2025). When to Use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation. arXiv / GraphRAG-Bench. [phase6-xiang-2025-when-to-use-graphs-rag](https://arxiv.org/abs/2506.05690) — academic; preprint_benchmark; candidate; mentions: 2.
8. Nicolas Matentzoglu; Nomi L. Harris; James P. Balhoff; et al. (2022). Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies. Database. [phase7-ontology-development-kit-toolkit-2022](https://doi.org/10.1093/database/baac087) — academic; peer_reviewed; candidate; mentions: 2.
9. Robert C. Jackson; James P. Balhoff; Emily Douglass; Nomi L. Harris; Christopher J. Mungall; James A. Overton (2019). ROBOT: A Tool for Automating Ontology Workflows. BMC Bioinformatics. [phase7-robot-automating-ontology-workflows-2019](https://doi.org/10.1186/s12859-019-3002-3) — academic; peer_reviewed; candidate; mentions: 2.
10. W3C RDF Data Shapes Working Group (2017). Shapes Constraint Language (SHACL). World Wide Web Consortium Recommendation. [w3c_shacl_2017](https://www.w3.org/TR/shacl) — technical; official_standard; core; mentions: 2.
11. Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, Xindong Wu (2023). Unifying Large Language Models and Knowledge Graphs: A Roadmap. arXiv. [arxiv-2306-08302v3](https://arxiv.org/abs/2306.08302) — academic; peer_reviewed_survey; core; mentions: 1.
12. Franz Baader; Diego Calvanese; Deborah McGuinness; Daniele Nardi; Peter Patel-Schneider (2003). The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press. [core-baader-2003-description-logic-handbook](https://www.cambridge.org/core/books/description-logic-handbook) — books; scholarly_book; core; mentions: 1.
13. ISO/IEC (2021). Information technology - Top-level ontologies - Part 2: Basic Formal Ontology (BFO). ISO/IEC. [core-bfo-iso-21838-2](https://www.iso.org/standard/74572.html) — technical; official_standard; core; mentions: 1.
14. Darren Edge; Ha Trinh; Newman Cheng; Joshua Bradley; Alex Chao; Apurva Mody; Steven Truitt; Jonathan Larson (2024). From Local to Global: A Graph RAG Approach to Query-Focused Summarization. arXiv / Microsoft Research. [core-edge-2024-graphrag](https://arxiv.org/abs/2404.16130) — academic; primary_source; core; mentions: 1.
15. The Gene Ontology Consortium (2000). Gene Ontology: Tool for the Unification of Biology. Nature Genetics. [core-gene-ontology-2000](https://doi.org/10.1038/75556) — academic; peer_reviewed_seminal; core; mentions: 1.
16. Thomas R. Gruber (1993). A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition. [core-gruber-1993-portable-ontology](https://doi.org/10.1006/knac.1993.1008) — academic; peer_reviewed_seminal; core; mentions: 1.
17. Nicola Guarino (1998). Formal Ontology in Information Systems. FOIS. [core-guarino-1998-formal-ontology-information-systems](https://dl.acm.org/doi/10.5555/521720.521722) — academic; peer_reviewed_seminal; core; mentions: 1.
18. Patrick Lewis; Ethan Perez; Aleksandra Piktus; Fabio Petroni; Vladimir Karpukhin; Naman Goyal; Heinrich Kuttler; Mike Lewis; Wen-tau Yih; Tim Rocktaschel; Sebastian Riedel; Douwe Kiela (2020). Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. NeurIPS. [core-lewis-2020-rag](https://arxiv.org/abs/2005.11401) — academic; peer_reviewed_seminal; core; mentions: 1.
19. Natalya F. Noy; Deborah L. McGuinness (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory. [core-noy-mcguinness-2001-ontology-101](https://protege.stanford.edu/publications/ontology_development/ontology101.pdf) — technical; widely_cited; core; mentions: 1.
20. Palantir Technologies (2026). AIP overview. Palantir Foundry Documentation. [core-palantir-aip-overview-2026](https://palantir.com/docs/foundry/aip/overview) — palantir; official_docs; core; mentions: 1.
21. Palantir Technologies (2026). Ontology building: Overview. Palantir Foundry Documentation. [core-palantir-ontology-overview-2026](https://www.palantir.com/docs/foundry/ontology/overview) — palantir; official_docs; core; mentions: 1.
22. W3C OWL Working Group (2012). OWL 2 Web Ontology Language Document Overview. W3C. [core-w3c-owl2-overview](https://www.w3.org/TR/owl2-overview) — technical; official_standard; core; mentions: 1.
23. W3C (2014). RDF 1.1 Concepts and Abstract Syntax. W3C. [core-w3c-rdf-11-concepts](https://www.w3.org/TR/rdf11-concepts) — technical; official_standard; core; mentions: 1.
24. W3C SPARQL Working Group (2013). SPARQL 1.1 Query Language. W3C. [core-w3c-sparql-11-query](https://www.w3.org/TR/sparql11-query) — technical; official_standard; core; mentions: 1.
25. Mariano Fernandez-Lopez, Asuncion Gomez-Perez, and Natalia Juristo (1997). METHONTOLOGY: From Ontological Art Towards Ontological Engineering. AAAI Spring Symposium Series. [fernandez_lopez_gomez_perez_juristo_1997_methontology](https://aaai.org/papers/0005-ss97-06-005-methontology-from-ontological-art-towards-ontological-engineering) — academic; widely_cited; candidate; mentions: 1.
26. Nicola Guarino, Daniel Oberle, and Steffen Staab (2009). What Is an Ontology?. Handbook on Ontologies, Springer. [guarino_oberle_staab_2009_what_is_ontology](https://doi.org/10.1007/978-3-540-92673-3_0) — academic; peer_reviewed; candidate; mentions: 1.
27. Nicola Guarino and Christopher A. Welty (2002). Evaluating Ontological Decisions with OntoClean. Communications of the ACM. [guarino_welty_2002_ontoclean](https://doi.org/10.1145/503124.503150) — academic; widely_cited; candidate; mentions: 1.
28. NHS England (2026). NHS Federated Data Platform: Contract explainer. NHS England. [nhs-fdp-contract-explainer-2026](https://www.england.nhs.uk/digitaltechnology/nhs-federated-data-platform/security-privacy/contract-explainer) — technical; primary_source; candidate; mentions: 1.
29. Natalya F. Noy, Nigam H. Shah, Patricia L. Whetzel, et al. (2009). BioPortal: Ontologies and Integrated Data Resources at the Click of a Mouse. Nucleic Acids Research. [noy_etal_2009_bioportal](https://doi.org/10.1093/nar/gkp440) — academic; peer_reviewed; candidate; mentions: 1.
30. Thomas Gruber (1995). Toward principles for the design of ontologies used for knowledge sharing?. International Journal of Human-Computer Studies. [oa-https-doi-org-10-1006-ijhc-1995-1081](https://doi.org/10.1006/ijhc.1995.1081) — academic; peer_reviewed_seminal; core; mentions: 1.
31. Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu (2021). A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. IEEE Transactions on Neural Networks and Learning Systems. [oa-https-doi-org-10-1109-tnnls-2021-3070843](https://ieeexplore.ieee.org/document/9416312) — academic; peer_reviewed_survey; core; mentions: 1.
32. Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d’Amato, Gerard de Melo, Claudio Gutiérrez, Sabrina Kirrane, José Emilio Labra Gayo (2021). Knowledge Graphs. ACM Computing Surveys. [oa-https-doi-org-10-1145-3447772](https://dl.acm.org/doi/10.1145/3447772) — academic; peer_reviewed_survey; core; mentions: 1.
33. Hamed Babaei Giglou; Jennifer D'Souza; Sören Auer (2023). LLMs4OL: Large Language Models for Ontology Learning. arXiv. [ont-ai-004](https://arxiv.org/abs/2307.16648) — academic; peer_reviewed; core; mentions: 1.
34. Mingyang Liang; et al. (2024). KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation. arXiv. [ont-ai-024](https://arxiv.org/abs/2409.13731) — academic; secondary_source; core; mentions: 1.
35. Tanay Aggarwal; Angelo Salatino; Francesco Osborne; Enrico Motta (2025). Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Field. Information Processing & Management / arXiv. [p2-llm-ont-006](https://doi.org/10.1016/j.ipm.2025.104262) — academic; peer_reviewed; candidate; mentions: 1.
36. Giovanni Ciatto; Andrea Agiollo; Matteo Magnini; Andrea Omicini (2025). Large language models as oracles for instantiating ontologies with domain-specific knowledge. Knowledge-Based Systems. [p2-llm-ont-007](https://arxiv.org/abs/2404.04108) — academic; peer_reviewed; candidate; mentions: 1.
37. Preston Rasmussen; Pavlo Paliychuk; Travis Beauvais; Jack Ryan; Daniel Chalef (2025). Zep: A Temporal Knowledge Graph Architecture for Agent Memory. arXiv. [p2-llm-ont-029](https://arxiv.org/abs/2501.13956) — technical; preprint; low_priority; mentions: 1.
38. Antonio De Santis; Marco Balduini; Federico De Santis; Andrea Proia; Arsenio Leo; Marco Brambilla; Emanuele Della Valle (2024). Integrating Large Language Models and Knowledge Graphs for Extraction and Validation of Textual Test Data. ISWC 2024 In-Use Track / arXiv. [p2-llm-ont-030](https://arxiv.org/abs/2408.01700) — academic; peer_reviewed; candidate; mentions: 1.
39. World Wide Web Consortium (2024). Data Catalog Vocabulary (DCAT) - Version 3. W3C Recommendation. [p2-llm-ont-032](https://www.w3.org/TR/vocab-dcat-3) — technical; official_standard; candidate; mentions: 1.
40. Palantir Technologies (2026). AI ethics and governance. Palantir Foundry Documentation. [pal-doc-aip-ethics-governance-2026](https://palantir.com/docs/foundry/aip/ethics-governance) — palantir; official_docs; core; mentions: 1.
41. Mohamed Ali; Zaki Taha; Mohamed Mabrouk Morsey (2026). Ontology-grounded knowledge graphs for mitigating hallucinations in large language models for clinical question answering. Journal of Biomedical Informatics. [phase11-ali-2026-ontology-grounded-kg-clinical-hallucinations](https://doi.org/10.1016/j.jbi.2026.104993) — academic; peer_reviewed; candidate; mentions: 1.
42. Ahmed Abdeen Hamed; Luis M. Rocha (2026). Protocol for evaluating ChatGPT in biomedical association generation and verification using a RAG-enabled, cross-model majority voting workflow. STAR Protocols. [phase11-hamed-rocha-2026-biomedical-rag-majority-voting-verification-protocol](https://doi.org/10.1016/j.xpro.2026.104533) — academic; peer_reviewed; candidate; mentions: 1.
43. Anupam Joshi; Tim Finin; Karuna Pande Joshi; Lalana Kagal (2026). Deontic Policies for Runtime Governance of Agentic AI Systems. arXiv. [phase11-joshi-2026-deontic-policies-agentic-ai-runtime-governance](https://arxiv.org/abs/2606.19464) — academic; preprint; candidate; mentions: 1.
44. Thanh Luong Tuan; Abhijit Sanyal (2026). Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification. arXiv. [phase11-tuan-sanyal-2026-predeployment-assurance-ontology-simulation](https://arxiv.org/abs/2606.04037) — academic; preprint_benchmark; candidate; mentions: 1.
45. Chuanjie Wu; Zhishang Xiang; Yunbo Tang; Zerui Chen; Qinggang Zhang; Jinsong Su (2026). MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation. arXiv / KDD 2026 accepted preprint. [phase11-wu-2026-memgraphrag-memory-multi-agent-graphrag](https://arxiv.org/abs/2606.00610) — academic; preprint; candidate; mentions: 1.
46. Diego Calvanese; Benjamin Cogrel; Sarah Komla-Ebri; Roman Kontchakov; Davide Lanti; Martin Rezk; Mariano Rodriguez-Muro; Guohui Xiao (2016). Ontop: Answering SPARQL queries over relational databases. Semantic Web. [phase14-calvanese-2016-ontop-answering-sparql-relational-databases](https://doi.org/10.3233/SW-160217) — academic; peer_reviewed; candidate; mentions: 1.
47. Mubashara Akhtar; Omar Benjelloun; Costanza Conforti; Luca Foschini; Pieter Gijsbers; Joan Giner-Miguelez; Sujata Goswami; Nitisha Jain; Michalis Karamousadakis; Michael Kuchnik; et al. (2024). Croissant: A Metadata Format for ML-Ready Datasets. ACM DEEM. [phase14-croissant-ml-ready-dataset-metadata-2024](https://doi.org/10.1145/3650203.3663326) — academic; peer_reviewed_survey; core; mentions: 1.
48. R. V. Guha; Dan Brickley; Steve Macbeth (2016). Schema.org: Evolution of Structured Data on the Web. ACM Queue. [phase14-schemaorg-evolution-structured-data-web-2016](https://doi.org/10.1145/2857274.2857276) — academic; peer_reviewed; candidate; mentions: 1.
49. Denny Vrandečić; Markus Krötzsch (2014). Wikidata: a free collaborative knowledgebase. Communications of the ACM. [phase14-wikidata-free-collaborative-knowledgebase-2014](https://doi.org/10.1145/2629489) — academic; peer_reviewed; candidate; mentions: 1.
50. Guohui Xiao; Diego Calvanese; Roman Kontchakov; Domenico Lembo; Antonella Poggi; Riccardo Rosati; Michael Zakharyaschev (2018). Ontology-Based Data Access: A Survey. IJCAI. [phase14-xiao-2018-ontology-based-data-access-survey](https://www.ijcai.org/proceedings/2018/0777.pdf) — academic; peer_reviewed_survey; core; mentions: 1.
51. Julián Arenas-Guerrero; David Chaves-Fraga; Jhon Toledo; María S. Pérez; Óscar Corcho (2024). Morph-KGC: Scalable knowledge graph materialization with mapping partitions. Semantic Web. [phase15-arenas-2024-morph-kgc-scalable-kg-materialization](https://doi.org/10.3233/SW-223135) — academic; peer_reviewed; candidate; mentions: 1.
52. Allyson L. Lister; Susanna-Assunta Sansone; et al. (2019). FAIRsharing as a Community Approach to Standards, Repositories and Policies. Nature Biotechnology. [phase16-fairsharing-community-standards-repositories-policies-2019](https://doi.org/10.1038/s41587-019-0080-8) — academic; peer_reviewed; candidate; mentions: 1.
53. Robert Stevens; et al. (2017). MIRO: Guidelines for Minimum Information for the Reporting of an Ontology. Journal of Biomedical Semantics. [phase16-miro-guidelines-minimum-information-reporting-ontology-2017](https://doi.org/10.1186/s13326-017-0172-7) — academic; peer_reviewed; candidate; mentions: 1.
54. Natalya F. Noy; Michel Klein (2004). Ontology Evolution: Not the Same as Schema Evolution. Web Semantics: Science, Services and Agents on the World Wide Web. [phase16-noy-klein-2004-ontology-evolution-schema-evolution](https://www.sciencedirect.com/science/article/pii/S1570826804000224) — academic; widely_cited; candidate; mentions: 1.
55. Zhangcheng Qiang; Weiqing Wang; Kerry Taylor (2023). Agent-OM: Leveraging LLM Agents for Ontology Matching. arXiv / PVLDB version available. [phase2-agent-om-2023](https://arxiv.org/abs/2312.00326) — academic; peer_reviewed; core; mentions: 1.
56. European Parliament and Council of the European Union (2024). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union. [phase2-eu-ai-act-2024](https://eur-lex.europa.eu/eli/reg/2024/1689/oj) — technical; official_standard; core; mentions: 1.
57. Hamed Babaei Giglou; Jennifer D'Souza; Felix Engel; Soren Auer (2024). LLMs4OM: Matching Ontologies with Large Language Models. arXiv / ESWC. [phase2-llms4om-2024](https://arxiv.org/abs/2404.10317) — academic; peer_reviewed; core; mentions: 1.
58. National Institute of Standards and Technology (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). NIST. [phase2-nist-ai-rmf-1-0-2023](https://www.nist.gov/itl/ai-risk-management-framework) — technical; official_standard; core; mentions: 1.
59. Palantir Technologies (2026). AIP Evals: Evaluate Ontology edits. Palantir Foundry Documentation. [phase2-pal-aip-evals-ontology-edits-2026](https://palantir.com/docs/foundry/aip-evals/ontology-edits) — palantir; official_docs; core; mentions: 1.
60. Palantir Technologies (2026). AIP observability: Overview. Palantir Foundry Documentation. [phase2-pal-aip-observability-overview-2026](https://palantir.com/docs/foundry/aip-observability/overview) — palantir; official_docs; core; mentions: 1.
61. Palantir Technologies (2026). Ontology MCP (OMCP) overview. Palantir Foundry Documentation. [phase2-pal-ontology-mcp-overview-2026](https://palantir.com/docs/foundry/ontology-mcp/overview) — palantir; official_docs; core; mentions: 1.
62. Maria Poveda-Villalon; Asuncion Gomez-Perez; Mari Carmen Suarez-Figueroa (2014). OOPS! (OntOlogy Pitfall Scanner!): An On-line Tool for Ontology Evaluation. International Journal on Semantic Web and Information Systems. [phase2-poveda-2014-oops](https://doi.org/10.1007/s13740-014-0028-y) — academic; peer_reviewed; candidate; mentions: 1.
63. W3C Provenance Working Group (2013). PROV-O: The PROV Ontology. W3C. [phase2-w3c-prov-o-2013](https://www.w3.org/TR/prov-o) — technical; official_standard; core; mentions: 1.
64. Geoffrey C. Bowker and Susan Leigh Star (1999). Sorting Things Out: Classification and Its Consequences. MIT Press. [phase3-bowker-star-1999-sorting-things-out](https://mitpress.mit.edu/9780262522953/sorting-things-out) — books; widely_cited; candidate; mentions: 1.
65. Graph-based Agent Memory survey authors (2026). Graph-based Agent Memory: Taxonomy, Techniques, and Evaluation. arXiv. [phase3-llm-ontmem-018](https://arxiv.org/abs/2602.05665) — academic; peer_reviewed_survey; candidate; mentions: 1.
66. LLM-empowered KGC survey authors (2025). LLM-empowered Knowledge Graph Construction: A Survey. arXiv. [phase3-llm-ontmem-023](https://arxiv.org/abs/2510.20345) — academic; peer_reviewed_survey; candidate; mentions: 1.
67. Semantic Layers for Reliable LLM-Powered Data Analytics authors (2026). Semantic Layers for Reliable LLM-Powered Data Analytics. arXiv. [phase3-llm-ontmem-024](https://arxiv.org/abs/2604.25149) — academic; preprint; low_priority; mentions: 1.
68. Helen Nissenbaum (2010). Privacy in Context: Technology, Policy, and the Integrity of Social Life. Stanford University Press. [phase3-nissenbaum-2010-privacy-context](https://www.sup.org/books/title?id=8862) — books; widely_cited; candidate; mentions: 1.
69. Palantir Technologies (2026). Palantir MCP: Installation. Palantir Foundry Documentation. [phase3-pal-mcp-installation-2026](https://palantir.com/docs/foundry/palantir-mcp/installation) — palantir; official_docs; core; mentions: 1.
70. Palantir Technologies (2026). Palantir MCP: Security - Data governance. Palantir Foundry Documentation. [phase3-pal-mcp-security-2026](https://palantir.com/docs/foundry/palantir-mcp/security) — palantir; official_docs; core; mentions: 1.
71. Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White, Margaret Mitchell, Timnit Gebru, Ben Hutchinson, Jamila Smith-Loud, Daniel Theron, and Parker Barnes (2020). Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing. ACM Conference on Fairness, Accountability, and Transparency. [phase3-raji-etal-2020-accountability-gap](https://doi.org/10.1145/3351095.3372873) — academic; peer_reviewed; candidate; mentions: 1.
72. Andrew D. Selbst, Danah Boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, and Janet Vertesi (2019). Fairness and Abstraction in Sociotechnical Systems. ACM Conference on Fairness, Accountability, and Transparency. [phase3-selbst-etal-2019-fairness-abstraction](https://doi.org/10.1145/3287560.3287598) — academic; widely_cited; candidate; mentions: 1.
73. Susan Leigh Star and James R. Griesemer (1989). Institutional Ecology, 'Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39. Social Studies of Science. [phase3-star-griesemer-1989-boundary-objects](https://doi.org/10.1177/030631289019003001) — academic; widely_cited; candidate; mentions: 1.
74. Susan Leigh Star and Karen Ruhleder (1996). Steps Toward an Ecology of Infrastructure: Design and Access for Large Information Spaces. Information Systems Research. [phase3-star-ruhleder-1996-ecology-infrastructure](https://doi.org/10.1287/isre.7.1.111) — academic; widely_cited; candidate; mentions: 1.
75. Databricks (2026). AI/BI Genie spaces and semantic model documentation. Databricks Documentation. [phase4-enterprise-databricks-genie-semantic-model-2026](https://docs.databricks.com/en/genie/index.html) — commercial; marketing; low_priority; mentions: 1.
76. data.world (2026). data.world AI Context Engine and knowledge graph catalog materials. data.world Resources. [phase4-enterprise-dataworld-ai-context-engine-2026](https://data.world/solutions/ai-context-engine) — commercial; marketing; low_priority; mentions: 1.
77. dbt Labs (2026). dbt Semantic Layer documentation. dbt Documentation. [phase4-enterprise-dbt-semantic-layer-2026](https://docs.getdbt.com/docs/use-dbt-semantic-layer/dbt-sl) — commercial; marketing; low_priority; mentions: 1.
78. Google Cloud (2026). Looker semantic model and Gemini in Looker documentation. Google Cloud Documentation. [phase4-enterprise-google-looker-semantic-model-gemini-2026](https://cloud.google.com/looker/docs/semantic-model) — commercial; marketing; low_priority; mentions: 1.
79. Microsoft (2026). Power BI semantic models and Copilot/Fabric data agent documentation. Microsoft Learn. [phase4-enterprise-microsoft-fabric-semantic-model-copilot-2026](https://learn.microsoft.com/en-us/fabric/data-science/concept-data-agent) — commercial; marketing; low_priority; mentions: 1.
80. Runxuan Liu; Bei Luo; Jiaqi Li; Baoxin Wang; Ming Liu; Dayong Wu; Shijin Wang; Bing Qin (2025). Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering. ACL 2025. [phase5-liu-2025-ontology-guided-reverse-thinking-kgqa](https://aclanthology.org/2025.acl-long.741) — academic; peer_reviewed; candidate; mentions: 1.
81. Palantir Technologies (2026). Connecting Agents to Decisions. Palantir Blog. [phase5-palantir-connecting-agents-decisions-2026](https://blog.palantir.com/connecting-agents-to-decisions-277dee8ddb40) — palantir; primary_source; core; mentions: 1.
82. Palantir Technologies (2026). Foundry platform summary for LLMs. Palantir Foundry Documentation. [phase5-palantir-foundry-platform-summary-llm-2026](https://www.palantir.com/docs/foundry/getting-started/foundry-platform-summary-llm) — palantir; official_docs; core; mentions: 1.
83. Palantir Technologies (2026). Discover and manage Ontology MCP servers in MCP Hub. Palantir Foundry Announcements. [phase5-palantir-mcp-hub-announcement-2026](https://www.palantir.com/docs/foundry/announcements/2026-05) — palantir; official_docs; core; mentions: 1.
84. Anna Sofia Lippolis; Mohammad Javad Saeedizade; Robin Keskisarkka; Aldo Gangemi; Eva Blomqvist; Andrea Giovanni Nuzzolese (2025). Assessing the Capability of Large Language Models for Domain-Specific Ontology Generation. ELMKE workshop at ESWC 2025 / arXiv. [phase6-lippolis-2025-domain-specific-ontology-generation-llms](https://arxiv.org/abs/2504.17402) — academic; preprint; candidate; mentions: 1.
85. NHS England / UK Contracts Finder (2024). Federated Data Platform and Associated Services. Contracts Finder. [phase6-nhs-fdp-contracts-finder-2024](https://www.contractsfinder.service.gov.uk/Notice/0f8a65b5-23a2-4294-abb1-a7fd8efb3ad0) — palantir; primary_source; candidate; mentions: 1.
86. NHS England (2026). FDP Data Protection Impact Assessment: NDIT Identifiable Version v3.0. NHS England. [phase6-nhs-ndit-fdp-dpia-2026](https://www.england.nhs.uk/wp-content/uploads/2025/08/redacted-ndit-nhs-england-fdp-dpia-identifiable-version-v3.0.pdf) — palantir; primary_source; core; mentions: 1.
87. A. Oarga; M. Hart; A. M. Bran; M. Lederbauer; P. Schwaller (2026). Scientific Knowledge Graph and Ontology Generation Using Open Large Language Models. Digital Discovery / Royal Society of Chemistry. [phase6-oarga-2026-scientific-kg-ontology-open-llms](https://pubs.rsc.org/en/content/articlelanding/2026/dd/d5dd00275c) — academic; peer_reviewed; candidate; mentions: 1.
88. Yihang Zhao (2025). Leveraging Large Language Models for Ontology Requirements Engineering. ESWC 2025 Satellite Events / LNCS. [phase6-zhao-2025-llm-ontology-requirements-engineering](https://doi.org/10.1007/978-3-031-99554-5_40) — academic; peer_reviewed; candidate; mentions: 1.
89. Dongzhuoran Zhou; Yuqicheng Zhu; Yuan He; Jiaoyan Chen; Evgeny Kharlamov; Steffen Staab (2025). Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness. arXiv. [phase6-zhou-2025-kg-rag-incompleteness](https://arxiv.org/abs/2504.05163) — academic; preprint; candidate; mentions: 1.
90. Charles Tapley Hoyt; et al. (2022). Unifying the identification of biomedical entities with the Bioregistry. Scientific Data. [phase7-bioregistry-biomedical-entity-identification-2022](https://doi.org/10.1038/s41597-022-01807-3) — academic; peer_reviewed; candidate; mentions: 1.
91. The Gene Ontology Consortium (2023). The Gene Ontology knowledgebase in 2023. GENETICS. [phase7-gene-ontology-knowledgebase-2023](https://doi.org/10.1093/genetics/iyad031) — academic; peer_reviewed; candidate; mentions: 1.
92. The Gene Ontology Consortium and collaborators (2019). Gene Ontology Causal Activity Modeling (GO-CAM) moves beyond GO annotations to structured descriptions of biological functions and systems. Nature Genetics. [phase7-go-cam-causal-activity-modeling-2019](https://doi.org/10.1038/s41588-019-0500-1) — academic; peer_reviewed; candidate; mentions: 1.
93. OBO Foundry contributors (2021). OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies. Database. [phase7-obo-foundry-2021-operationalizing-open-data-principles](https://doi.org/10.1093/database/baab069) — academic; peer_reviewed; candidate; mentions: 1.
94. OLS4 contributors / EMBL-EBI (2025). OLS4: a new Ontology Lookup Service for a growing interdisciplinary knowledge ecosystem. Bioinformatics. [phase7-ols4-ontology-lookup-service-2025](https://doi.org/10.1093/bioinformatics/btaf279) — academic; peer_reviewed; candidate; mentions: 1.
95. Jie Zheng; Zuoshuang Xiang; Jie Lin; et al. (2016). Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration. Nucleic Acids Research. [phase7-ontobee-linked-ontology-server-2016](https://doi.org/10.1093/nar/gkw918) — academic; peer_reviewed; candidate; mentions: 1.
96. Barry Smith, Michael Ashburner, Cornelius Rosse, et al. (2007). The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration. Nature Biotechnology. [smith_etal_2007_obo_foundry](https://doi.org/10.1038/nbt1346) — academic; peer_reviewed; candidate; mentions: 1.
97. Mari Carmen Suarez-Figueroa, Asuncion Gomez-Perez, and Mariano Fernandez-Lopez (2015). A Scenario-Based Methodology for Ontology Development. Applied Ontology. [suarez_figueroa_2015_neon](https://doi.org/10.3233/AO-150145) — academic; peer_reviewed; low_priority; mentions: 1.
98. W3C Semantic Web Deployment Working Group (2009). SKOS Simple Knowledge Organization System Reference. World Wide Web Consortium Recommendation. [w3c_skos_reference_2009](https://www.w3.org/TR/skos-reference) — technical; official_standard; core; mentions: 1.
99. Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, et al. (2016). The FAIR Guiding Principles for Scientific Data Management and Stewardship. Scientific Data. [wilkinson_etal_2016_fair](https://doi.org/10.1038/sdata.2016.18) — academic; peer_reviewed; candidate; mentions: 1.