Bitcoin Transaction Network Files

This dataset contains transaction edge files from block 0 to block 737900. Block times are given in the bitcoin_times.csv file (US Central time). The data is divided into ten splits. Each split's data is zipped together and contains 73600 block edge files of transactions that were mined in the blocks of that splitting scope. Each .Csv file contains the information for 100 blocks. The data was parsed by the Bitcoin-ETL library of Google (https://github.com/blockchain-etl/bitcoin-etl). Some transaction outputs do not follow the protocol, and get labeled as nonstandard by the ETL library. In such outputs the addresses cannot be parsed. We give them with the nonstandard tag such as nonstandard98a1069f93253f2dcf24e989c69c53447fa0870c.
Each line in the input edge file is tab-separated with the format:

Consider the Bitcoin graph in the figure above, where transactions are shown with rectangles and addresses are shown with circles. There are four transactions and 13 addresses. This graph would be given in two files: blockID_in.csv and blockID_out.csv. Below, we show the content of each file. Note that we list previous (unknown) transactions with t_x* notation (For example t_x1, t_x2 are not shown in the network figure because they have appeared in the earlier blocks).

-- blockID_in.csv
BlockHeightOft_1 HashOft_1 2 a1 1 a2 1
BlockHeightOft_2 HashOft_2 3 a3 2 a4 1 a5 1
BlockHeightOft_3 HashOft_3 1 a7 0.8
BlockHeightOft_4 HashOft_4 2 a11 0.3 a8 3.8

-- blockID_out.csv
BlockHeightOft_1	HashOft_1	2	a_6	10^8	a_7	0.8^0.8
BlockHeightOft_2	HashOft_2	1	a_8	3.8*10^8
BlockHeightOft_3	HashOft_3	3	a_9	0.2*10^8	a_10	0.2*10^8	a_11	0.3*10^8
BlockHeightOft_4	HashOft_4	2	a_12	3.7*10^8	a_13	0.3*10^8

Sample Dataset

Use one of the block splits as sample data.

Full Dataset

	@inproceedings{chartalistNeurips2022,
  author    = {Kiarash Shamsi and Yulia R. Gel and  Murat Kantarcioglu and Cuneyt G. Akcora},
  title     = {Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains},
  booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference
               on Neural Information Processing Systems 2022, NeurIPS 2022, November 29-December
               1, 2022, New Orleans, LA, USA},
  pages     = {1--14},
  year      = {2022},
  url       = {https://openreview.net/pdf?id=10iA3OowAV3}
  }