- CSV2FAIR_KG transforms tabular data (CSV) into a Findable, Accessible, Interoperable and Reusable (FAIR) knowledge graph (KG) for biomedical research. It integrates ontology mapping, metadata enrichment, Persistent Identifier (PID) assignment and graph construction for semantic applications.
- RAG-interface is the user interface for the FAIR GraphRAG system and a Next.js project bootstrapped with
create-next-app. An LLM serves as a chatbot and enables querying a knowledge graph stored in Neo4j for data analysis purposes.
If you use fair-graphrag in your research or application, please cite the following:
Flüh, M. (2025). FAIR GraphRAG: A Retrieval-Augmented Generation Approach for Semantic Data Analysis.
A formal citation file is included as CITATION.cff for automated reference managers and repositories.
This project is licensed under the MIT License. You are free to use, modify, and distribute this software with attribution.
- Title: fair-graphrag
- Description: A pipeline for converting biomedical tabular data into FAIR-compliant knowledge graphs using methods for FAIRification and graph construction.
- Keywords: FAIR Principles, knowledge graph construction, large language model
- Provenance Repository: https://github.com/FAIR-GraphRAG/CSV2FAIR_KG
- Authors: Marlena Flüh
- Repository Copied On: 24 September, 2025
- License: MIT