Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains

Part of Advances in Neural Information Processing Systems 35 (NeurIPS 2022) Datasets and Benchmarks Track

Bibtex Paper Supplemental


Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia Gel, Cuneyt G Akcora


Machine learning on blockchain graphs is an emerging field with many applications such as ransomware payment tracking, price manipulation analysis, and money laundering detection. However, analyzing blockchain data requires domain expertise and computational resources, which pose a significant barrier and hinder advancement in this field. We introduce Chartalist, the first comprehensive platform to methodically access and use machine learning across a large selection of blockchains to address this challenge. Chartalist contains ML-ready datasets from unspent transaction output (UTXO) (e.g., Bitcoin) and account-based blockchains (e.g., Ethereum). We envision that Chartalist can facilitate data modeling, analysis, and representation of blockchain data and attract a wider community of scientists to analyze blockchains. Chartalist is an open-science initiative at