bio-ml / README.md
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BioML 2026 init — datasets + docs + SHA256SUMS + manifests
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---
license: other
license_name: bioml-2026-mixed
pretty_name: BioML 2026 (OAEI Bio-ML)
viewer: false
tags:
- ontology-matching
- ontology-alignment
- biomedical
- knowledge-graphs
- owl
- OAEI
- UMLS
- SNOMED-CT
size_categories:
- 10K<n<100K
---
# BioML 2026 — OAEI Bio-ML
The public task data for the **[OAEI](https://oaei.ontologymatching.org/) Bio-ML 2026** track (a larger LargeBio), over three whole-ontology pairs: **NCIT–DOID, SNOMED–FMA, SNOMED–NCIT**. This repository holds the **redistributable pieces** — the reference/candidate data as entity IRIs/CURIEs and the manifests. The ontologies themselves are **not re-hosted** (see [Ontologies](#ontologies)); the held-out test gold is organiser-side only; the scoring kit is code and lives in the [GitHub repo](https://github.com/liseda-lab/OAEI-Bio-ML) (see [Quickstart](#quickstart)). Ssee the [evaluation metrics](https://liseda-lab.github.io/OAEI-Bio-ML/evaluation/) on the track website.
## Tasks
- **Global equivalence alignment** — submit an OAEI Alignment RDF/XML or a TSV per pair. Scored (organiser-side) with repaired coherence-aware P/R/F1 (headline) + standard P/R/F1 + Global Coherence. A public `refs_equiv/train.tsv` of positive mappings is provided per pair.
- **Local equivalence ranking** — rank the 100-candidate pool per query. Scored with MRR + Hits@{1,5,10}.
## Layout (per pair `NCIT-DOID/`, `SNOMED-FMA/`, `SNOMED-NCIT/`)
| Path | Contents |
|---|---|
| `local.{train,valid,test}.cands.tsv` | Subtrack 2 ranking pools (100 cands/query; test is gold-stripped) |
| `refs_equiv/train.tsv` | Subtrack 1 public train positives (`SrcEntity, TgtEntity, Score`) |
| `repaired/` | the same set against the coherence-repaired reference |
| `evaluation/` | `sample_submission.tsv`, `submission_schema.json` (shared) |
| `SHA256SUMS.txt`, `release_manifest.json`, `license_manifest.json`, `resolved_versions.json` | integrity + provenance |
The **scoring kit** (validators + self-scorers, zero-install) is **code** and lives in the GitHub repository [`liseda-lab/OAEI-Bio-ML`](https://github.com/liseda-lab/OAEI-Bio-ML), not in this dataset.
## Coming from the original Bio-ML?
`local.*.cands.tsv` corresponds to Bio-ML's `refs_equiv/test.cands.tsv` (now a 3-way train/valid/test split, 100 cands/query). `refs_equiv/train.tsv` is the supervised positive-mapping file. The ontologies are **not** bundled here.
## Ontologies
The task uses the whole source ontologies; obtain them yourself (versions + checksums pinned in `resolved_versions.json`, instructions in `ontologies.md`): **NCIT, MONDO, DOID** are openly downloadable (CC BY / CC0); **SNOMED CT** and **UMLS** require your own UTS licence; **FMA** is downloadable from its source. See `license_manifest.json`.
## Quickstart
The scoring kit lives in the GitHub repo — clone it for the tools, download this dataset for the data:
```bash
git clone https://github.com/liseda-lab/OAEI-Bio-ML # provides scoring_kit/
pip install -U huggingface_hub
hf download OAEI-ML/bio-ml --repo-type dataset --revision 2026 --local-dir ./bio-ml # the data
python3 OAEI-Bio-ML/scoring_kit/self_check.py --data ./bio-ml # oracle -> perfect scores
python3 OAEI-Bio-ML/scoring_kit/validate_ranking.py bio-ml/NCIT-DOID/local.test.cands.tsv my_ranking.tsv
python3 OAEI-Bio-ML/scoring_kit/score_local.py my_ranking.tsv bio-ml/NCIT-DOID/local.valid.cands.tsv
```
Submit via the CodaBench competitions (linked from the track website).
## Licensing
The packaging and reference/candidate **IRI data** are provided for this evaluation and ontology-matching research. Underlying sources retain their licences: **NCIT, MONDO** CC BY 4.0; **DOID** CC0 1.0; **SNOMED CT** (Affiliate) and **UMLS** (Metathesaurus) are **restricted** (UTS) — their derived OWL/gold is not redistributed here; **NCIT, MONDO, DOID, FMA** are freely redistributable (OWL is pointer-only here, for size). Per-source details: `license_manifest.json`. Do not attempt to reconstruct the held-out test reference.
## Citation
Cite the OAEI Bio-ML 2026 track (details on the track website).