fairscape-conversion
Your metadata is already written down — as a datasheet, a datapackage, or a
workflow engine's run output. Convert it into a FAIRSCAPE/EVI RO-Crate
(ro-crate-metadata.json) instead of re-entering it. One command per format.
pip install -e . # from this directory; installs fairscape-conversion
The fairscape import / fairscape export commands come with the companion
fairscape CLI (not yet published). Without it, every conversion also runs as
python -m fairscape_conversion.core.cli convert <format> <import|export> IN [OUT].
Import — get an RO-Crate
Pick the row that matches what you have.
| You have | You need | Run |
|---|---|---|
| A Datasheet for Datasets (D4D) | the datasheet as YAML or JSON | fairscape import d4d datasheet.yaml -o ./crate |
| A CFDE C2M2 datapackage | the directory of TSVs + C2M2_datapackage.json |
fairscape import c2m2 ./datapackage-dir -o ./crate |
| A Workflow Run RO-Crate | its ro-crate-metadata.json |
fairscape import wrroc ro-crate-metadata.json -o ./crate |
| A finished Cromwell/WDL run | the file from cromwell run -m metadata.json |
fairscape import cromwell metadata.json -o ./crate |
| A finished Snakemake run | the records JSON from snakemake --reporter fairscape |
fairscape import snakemake records.json -o ./crate |
| Finished MLflow runs | the tracking store (an mlruns dir or tracking URI) and pip install mlflow |
fairscape import mlflow ./mlruns --experiment NAME -o ./crate |
Export — from an RO-Crate
| You want | Run |
|---|---|
| A D4D datasheet | fairscape export d4d ro-crate-metadata.json |
| A Workflow Run RO-Crate | fairscape export wrroc ro-crate-metadata.json |
| An MLCommons Croissant document | fairscape export croissant ro-crate-metadata.json |
Try it — no data needed
Every format ships a real example input and its expected output inside its plugin folder, so you can run any conversion right now:
fairscape import d4d plugins/d4d/input.yaml -o /tmp/crate
| format | example input | expected output |
|---|---|---|
| d4d | plugins/d4d/input.yaml (the AI-READI datasheet) |
plugins/d4d/golden.json |
| c2m2 | plugins/c2m2/input-datapackage/ (miniature datapackage) |
plugins/c2m2/golden.json |
| wrroc | plugins/wrroc/input.json (CWL revsort run crate) |
plugins/wrroc/golden.json |
| cromwell | plugins/cromwell/input.json (scatter workflow records) |
plugins/cromwell/golden.json |
| snakemake | plugins/snakemake/input.json (3-rule chain records) |
plugins/snakemake/golden.json |
| mlflow | plugins/mlflow/input.json (iris experiment records) |
plugins/mlflow/golden.json |
| croissant | plugins/croissant/input.json (export this crate) |
plugins/croissant/golden.json |
From Python
import yaml
from fairscape_conversion.plugins import d4d
crate = d4d.convert("import", yaml.safe_load(open("datasheet.yaml")))
Same shape for every format: wrroc, c2m2, cromwell, snakemake,
mlflow (convert("import", ...)), and d4d/wrroc/croissant
(convert("export", crate)).
More
- Your format isn't listed →
docs/NEW-PLUGIN.md— a converter is a folder of two CSVs plus a small plugin class. - How the engine works, what's tested →
docs/INTERNALS.mdandMAPPING-SCHEMA.md.
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