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Datasets:
COINjecture
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NPcommitments

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Tags:
blockchain
commitments
np-complete
proof-of-work
coinjecture
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                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
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                  return func(*args, **kwargs)
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                File "/src/services/worker/src/worker/utils.py", line 61, in get_rows
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              ValueError: Bad split: train. Available splits: ['test']

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COINjecture Commitments Dataset

This dataset contains cryptographic commitments from COINjecture Network B blockchain mining operations.

Overview

Commitments are created during the mining process where miners commit to NP-complete problem solutions without revealing them immediately. This enables:

  • Fair mining: Prevents front-running and solution stealing
  • Verifiable work: Solutions can be verified after commitment
  • Research data: Provides structured data for NP-complete problem research

Dataset Structure

Based on the baseline dataset COINjecture/v5, this dataset focuses specifically on commitment records.

Commitment Lifecycle

  1. Commitment Phase: Miner creates commitment hash = H(problem_params || salt || H(solution))
  2. Reveal Phase: Miner reveals solution after block is mined
  3. Verification: Network verifies commitment matches revealed solution

Schema

Each record contains:

  • commitment_id: Unique identifier
  • commitment_hash: Cryptographic hash of the commitment
  • problem_type: Type of NP-complete problem
  • problem_params: Problem parameters (JSON)
  • salt: Random salt for commitment
  • solution_hash: Hash of solution (H(solution))
  • solution_data: Actual solution (revealed later, null initially)
  • work_score: Computed work score
  • status: Current status (Committed, Revealed, Expired)

Usage

Loading the Dataset 

from datasets import load_dataset

# Load commitments dataset
dataset = load_dataset("COINjecture/commitments")

# Filter by status
committed = dataset.filter(lambda x: x["status"] == "Committed")
revealed = dataset.filter(lambda x: x["status"] == "Revealed")

# Filter by problem type
sat_commitments = dataset.filter(lambda x: x["problem_type"] == "SAT")

Analyzing Commitments 

# Count commitments by status
status_counts = dataset["train"].to_pandas()["status"].value_counts()

# Average work scores by problem type
avg_scores = dataset["train"].to_pandas().groupby("problem_type")["work_score"].mean()

Data Collection

Data is collected in real-time from COINjecture Network B blockchain nodes:

  • Commitments are recorded when blocks are mined
  • Solutions are revealed in subsequent blocks
  • All data is verified against blockchain state

Baseline Dataset

This dataset is based on COINjecture/v5 which contains:

  • Full problem solutions
  • Energy measurements
  • Mining metrics
  • Block metadata

The commitments dataset focuses specifically on the commitment/reveal mechanism.

License

MIT License - See LICENSE file for details.

Citation 

@dataset{coinjecture_commitments,
  title={COINjecture Commitments Dataset},
  author={COINjecture Network},
  year={2025},
  url={https://huggingface.co/datasets/COINjecture/commitments}
}

Contact

For issues or questions, please open an issue on the COINjecture GitHub repository.

Generated automatically by COINjecture Network B blockchain nodes

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