--- license: cc-by-4.0 task_categories: - other language: - en - zh tags: - traditional-chinese-medicine - biomedical - drug-discovery - knowledge-graph - computational-pharmacology configs: - config_name: nodes default: true data_files: original_kg/nodes.tsv sep: "\t" - config_name: edges data_files: original_kg/edges.tsv sep: "\t" --- # TCM-MKG ## Dataset Description TCM-MKG (Traditional Chinese Medicine Multidimensional Knowledge Graph) is a large-scale biomedical knowledge resource for Traditional Chinese Medicine (TCM)-related research. This repository is a Hugging Face distribution of the publicly released **TCM-MKG V1.0** dataset. It preserves the original Zenodo source tables and additionally provides a Hub-friendly tabular export under `original_kg/` for convenient machine access. This repository should be understood as a **format conversion and redistribution** of the released TCM-MKG data. It does **not** claim newly collected data, newly curated biomedical evidence, or a newly constructed knowledge graph. The underlying knowledge content comes from the original TCM-MKG authors and their integration of publicly available resources. The dataset can support research in: - Traditional Chinese Medicine knowledge representation - Knowledge graph reasoning and completion - Knowledge graph embedding - Drug discovery and drug repurposing - Network pharmacology - AI-assisted biomedical research ## Data Source The original dataset is: **Traditional Chinese Medicine Multidimensional Knowledge Graph (TCM-MKG V1.0)** Zenodo DOI: https://doi.org/10.5281/zenodo.13763953 The original Zenodo release provides the source tables `D1`-`D24`, the supplementary table `SD1`, and the accompanying documentation PDF. This Hugging Face release keeps those raw files and also exposes a tabular `nodes.tsv` / `edges.tsv` export for downstream knowledge graph and machine learning workflows. Users should cite the original dataset when using this resource. ## Files - `original_kg/nodes.tsv`: node table with columns `node_id`, `node_type`, `name`, `aliases`, `source_table`, and `extra_json` - `original_kg/edges.tsv`: edge table with columns `source_id`, `target_id`, `relation`, `source_table`, `evidence`, and `attributes_json` - `D1_*.tsv` to `D24_*.tsv`: original source-specific tables from the Zenodo release - `SD1_predicted_InChIKey_EntrezID.tsv`: supplementary source table from the Zenodo release - `TCM-MKG_Open_Source_Documentation.pdf`: original documentation file In this release, `original_kg/nodes.tsv` contains 369,912 rows and `original_kg/edges.tsv` contains 48,849,793 rows. ## Dataset Structure The dataset contains multidimensional biomedical knowledge related to: - TCM terminology - Chinese patent medicines - Chinese herbal pieces - Natural products and chemical identifiers - Biological targets - Diseases and ontology mappings - Protein-protein interactions The Hub-oriented graph export can be used as entity-relation-entity style data: - `nodes.tsv` stores normalized entity records - `edges.tsv` stores graph relations together with provenance through `source_table` and JSON attributes The `source_table` field links exported graph rows back to the original source-table identifiers such as `D3`, `D6`, or `D23`. ## Usage This dataset can be used for: - Knowledge graph completion - Entity and relation representation learning - Link prediction - Drug discovery and drug repurposing - Traditional Chinese Medicine mechanism exploration - Network pharmacology analysis - Biomedical knowledge graph research Example loading with Hugging Face `datasets`: ```python from datasets import load_dataset nodes = load_dataset("JX-Lab/TCM-MKG", "nodes", split="train") edges = load_dataset("JX-Lab/TCM-MKG", "edges", split="train", streaming=True) ``` For very large graph operations, streaming is recommended for `edges.tsv`. ## Citation If you use this dataset, please cite the original TCM-MKG dataset: ```bibtex @dataset{zeng_jingqi_2024_13763953, author = {Zeng, Jingqi and Jia, Xianpei}, title = {Traditional Chinese Medicine Multidimensional Knowledge Graph (TCM-MKG)}, year = {2024}, publisher = {Zenodo}, version = {V1.0}, doi = {10.5281/zenodo.13763953}, url = {https://doi.org/10.5281/zenodo.13763953} } ``` ## Disclaimer This repository provides a Hugging Face-compatible distribution of the publicly available TCM-MKG dataset. The original data were collected, integrated, and released by the original authors from publicly available resources. This repository does not claim ownership of the original data and should not be interpreted as introducing a newly built knowledge graph beyond format conversion for repository access. Users are responsible for complying with the original dataset license and for appropriately citing the original authors and original data sources when using this resource.