Dataset Card for CanadianInvertebrates-ML

Alternative names: InvertebratesCanada-ML, CanInv-ML, CanInv-1M, Canada-1.5M

Overview

The CanadianInvertebrates-ML is a machine learning-ready dataset derived from the raw DNA barcodes publiseh in deWaard et. al, 2019. The data is specifically designed and curated for different machine learning tasks in biodiversity analysis: species classification, genus identification of novel species, and BIN reconstruction.

Citation

If you make use of this dataset and/or its code repository, please cite the following paper:

cite as:

@misc{arias2025barcodeberttransformersbiodiversityanalysis,
      title={BarcodeBERT: Transformers for Biodiversity Analysis}, 
      author={Pablo Millan~Arias and Niousha Sadjadi and Monireh Safari and ZeMing Gong and Austin T. Wang and Joakim Bruslund Haurum and Iuliia Zarubiieva and Dirk Steinke and Lila Kari and Angel X. Chang and Scott C. Lowe and Graham W. Taylor},
      year={2025},
      eprint={2311.02401},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2311.02401}, 
}

Dataset content

Each specimen contains the following annotations:

Indexing fields
- processid: A unique number assigned by BOLD (International Barcode of Life Consortium).
- sampleid: A unique identifier given by the collector.
Taxonomic labels
- phylum, class, order, family, genus, species: Hierarchical taxonomic classification
Genetic information
- dna_bin: Barcode Index Number
- dna_barcode: DNA barcode sequence
Split and localization
- split: Data partition label (e.g., pretrain, train, test, val, test_unseen)

Sample Usage

To-Do

Dataset Sources

GitHub: https://github.com/bioscan-ml/BarcodeBERT
Zenodo: To-Do
Kaggle: ?
Paper: https://arxiv.org/abs/2311.02401