ERP Inventory Movement and State Invariant Validation Dataset

#inventory invariant validation #quantity conservation checking #location transition validation #batch traceability validation #available stock checking #ERP inventory management #warehouse operations #inventory reconciliation #inventory auditing

4250
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-03

AI Analysis & Value Prop

This dataset uses structured JSON to describe inventory receipts, issues, transfers, batch or location changes, and related inventory snapshots, covering common ERP inventory movement scenarios. Each example can be used to check constraints such as quantity conservation, source and destination location consistency, batch traceability, and stock availability, with machine-readable violations as output. It provides explicit validation signals for verifiable-reward reinforcement learning and supports inventory constraint validation, model training, and evaluation.

Dataset Insights

Sample Examples

{}

Technical Specifications

Field	Type	Description
file_name	string	File name
violations	array	Machine-readable violations found when validating the movement and its resulting inventory state.
movement_input	object	The original movement record and related inventory snapshots provided for validation.
validation_status	string	The overall result derived from the inventory invariant checks.
availability_check	object	A computed check that the movement does not consume more available stock than is held at the source location.
batch_traceability_valid	boolean	Indicates whether batch identifiers are tracked consistently between the movement and its inventory snapshots.
location_transition_valid	boolean	Indicates whether the recorded source and destination locations are consistent with the movement and inventory snapshots.
quantity_conservation_check	object	A computed comparison of the expected net quantity change with the actual change shown in the inventory snapshots.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What inventory scenarios does the dataset cover?: The JSON examples describe inventory receipts, issues, transfers, batch or location changes, and related inventory snapshots for validating common ERP inventory movement constraints.

Which rules can the data validate?: It supports checks for quantity conservation, source and destination location consistency, continuous batch identification, and whether a movement exceeds available stock at the source location. Results include an overall status and machine-readable violations.

Which training and evaluation tasks is it suitable for?: It is suitable for inventory constraint validation, structured business reasoning, and violation detection. It can also provide checkable outcome signals for verifiable-reward reinforcement learning.

How can I obtain the data, and what are the licensing terms?: Visit the dataset product page for access options, file specifications, and licensing information. Permitted use depends on the published license; confirm the applicable terms before commercial deployment or redistribution.

Can't find the data you need?

Post a request and let data providers reach out to you.

Get this Dataset

Verified for Enterprise Use

Cite this Work

@dataset{Mobiusi2026,
  title={ERP Inventory Movement and State Invariant Validation Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/010a5416212c840d5ed0a2ce7c5dd142},
  urldate={2026-10-22},
  keywords={ERP inventory dataset,inventory movement validation,inventory constraint checking,quantity conservation validation,batch traceability data,location transition validation,RLVR training data,inventory state validation},
  version={1.0}
}

Using this in research? Please cite us.

placeholder

Scene

Domain

Modality

Task