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VynFi/vynfi-supply-chain-ocel

VynFi Supply Chain OCEL (v5.29 SOTA mode) Native OCEL 2.0 event log for a 5-company manufacturing supply chain. Sister dataset to VynFi/vynfi-journal-entries-1m — same v5.29 generator, same SOTA-N behavioral lever stack + central ConcentrationPipeline, but materialised as an object-centric event log (events + objects + relationships) instead of a flat GL. Why four configs OCEL 2.0 is a multi-table schema by design. Selecting just one "default" split would lose… See the full description on the dataset page: https://huggingface.co/datasets/VynFi/vynfi-supply-chain-ocel.

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VynFi Supply Chain OCEL (v5.29 SOTA mode)

Native OCEL 2.0 event log for a 5-company manufacturing supply chain. Sister dataset to `VynFi/vynfi-journal-entries-1m` — same v5.29 generator, same SOTA-N behavioral lever stack + central ConcentrationPipeline, but materialised as an object-centric event log (events + objects + relationships) instead of a flat GL.

Why four configs

OCEL 2.0 is a multi-table schema by design. Selecting just one "default" split would lose 90 % of the signal. The four configs below are sized so each can be loaded independently for the analyses they support.

configrowswhat it is
events320,459the actual OCEL event log (timestamps + activity + linked objects)
objects7,439each entity / order / shipment / invoice with its lifecycle
anomaly_labels9,804per-event ground-truth labels (fraud / error / process anomalies)
document_events358document-flow milestones (PO opened, GR booked, IR matched, payment cleared)

Load with load_dataset(repo, name=<config_name>). The events config is the canonical OCEL log most process-mining tools (pm4py, ProM, Celonis) consume.

Structural quality (vs reference)

Same v5.29 SOTA lever stack as the JE datasets; see `vynfi-journal-entries-1m` for the 13-row structural-metric table. The lever effects propagate through the OCPM event-log construction (P2P/O2C process chains inherit the same SOTA-N behavioral patterns).

Dataset scope

  • 5 companies × 12 months × `Custom(300_000)` (heap cap raised to 64 GB for VM-class regen)
  • ~320 K OCEL events, ~7.4 K objects across P2P/O2C/manufacturing process types
  • Method-A flat edge list (je_network.parquet) joinable to events via shared document_id + entry date
  • Multi-currency (USD/EUR/SGD)

Quick start

python
from datasets import load_dataset

events = load_dataset("VynFi/vynfi-supply-chain-ocel", name="events")
objs   = load_dataset("VynFi/vynfi-supply-chain-ocel", name="objects")
print(events["train"].num_rows, "events")   # ~320,459
print(objs["train"].num_rows, "objects")    # ~7,439

For an end-to-end OCEL 2.0 file, the events + objects + relationships roll up into the ocel_json output the engine writes during generation; the parquet split here is for tabular consumers.

Generation config

configs/examples/hf/supply_chain_ocel_sota.yaml in `mivertowski/SyntheticData @ v5.29.0`.

bash
datasynth-data validate --config supply_chain_ocel_sota.yaml
datasynth-data generate --config supply_chain_ocel_sota.yaml

Reproducibility

artefactpath
Generatordatasynth-data 5.29.0 (release tag v5.29.0)
Configconfigs/examples/hf/supply_chain_ocel_sota.yaml
Run seed20260509 (preserved from v5.10 lineage)

Citation

bibtex
@dataset{vynfi_sc_ocel_2026,
  author    = {Ivertowski, Michael and DataSynth contributors},
  title     = {VynFi Supply Chain OCEL — v5.29 SOTA mode},
  year      = {2026},
  publisher = {VynFi / Hugging Face},
  url       = {https://huggingface.co/datasets/VynFi/vynfi-supply-chain-ocel},
  version   = {v5.29.0},
}