AnonNet Dataset

We present AnonNet, an anonymised real-world dataset capturing the structure of a large manufacturing supply network. The dataset consists of more than 7,000 nodes and 40,000 edges, where nodes represent individual companies and edges denote supply relationships. To preserve confidentiality, all company names have been anonymised, while rich node-level attributes are retained, including geographic location and product lists.

AnonNet provides researchers and practitioners with a unique opportunity to explore the topology, dynamics, and resilience of complex supply networks while ensuring data privacy. It is intended as a benchmark resource for advancing methods in network analysis, supply chain modelling, and industrial analytics.

Download

👉 The dataset are freely available on GitHub: AnonNet Dataset on GitHub

How to Cite

If you use this dataset in your research, please consider to cite the following paper:

Liming Xu, Yunbo Long, Alexandra Brintrup. AnonNet: An Anonymised Real-World Network for Supply Network Analysis, 2025.

@article{xu2025syndelay,
  title={AnonNet: An Anonymised Real-World Network for Supply Network Analysis},
  author={Xu, Liming and Long, Yunbo and Brintrup, Alexandra},
  year={2025}
}

⚠️ Disclaimer:
The datasets are provided "as-is" for informational and research purposes only. We make no guarantees regarding accuracy, completeness, or suitability for any specific application. Users are solely responsible for how they use the data, including compliance with relevant laws, regulations, and ethical guidelines. By accessing or downloading any dataset, you agree to use it at your own responsibility.