Datasets:

netrias
/

cancer_metadata_harmonization

license: apache-2.0
language:
  - en
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.csv
      - split: validation
        path: data/valid.csv
      - split: id_test
        path: data/id_test.csv
      - split: ood_test
        path: data/ood_test.csv
task_categories:
  - text2text-generation
  - text-generation
pretty_name: Cancer Metadata Harmonization Dataset

Cancer Metadata Harmonization Dataset

Summary

This dataset contains cancer-related terms for training and evaluating metadata harmonization systems in the biomedical domain. Each entry includes a term representation, its corresponding harmonized standard, and metadata such as semantic type, variation type, and source terminology. Term representations include standard forms as well as lexical variations (e.g., synonyms, abbreviations) and are harmonized to biomedical standards from NCIt, caDSR, GDC, ICD-O3, and MedDRA.

Note: This dataset includes a focused subset of semantic types:
Neoplastic Process, Disease or Syndrome, Finding, Laboratory Procedure, and Quantitative Concept.

This dataset was used in the study:

Metadata Harmonization from Biological Datasets with Language Models
Alexander Verbitsky, Patrick Boutet, Mohammed Eslami
Netrias, LLC

Supported Splits

The dataset includes the following splits:

train: Training data with aligned representation-standard pairs.
validation: Used for model selection and early stopping.
id_test: In-dictionary test set; contains new representations of standard terms present in the training set.
ood_test: Out-of-dictionary test set; contains representations of standard terms not present in the training set.

Features

Each example includes the following fields:

representation (string): The original term variant being harmonized. This may be a synonym, abbreviation, transformation, or the standard term itself.
harmonization_standard (string): The correct standardized form of the term, drawn from a controlled terminology.
variation_type (string): A label describing how the representation differs from the standard (e.g., “abbreviation”, “synonym”, or other transformation types).
semantic_type (string): The semantic category of the term (e.g., "Neoplastic Process", "Laboratory Procedure").
source_terminology (string): Comma-separated ontologies or terminologies where the standard term appears. Multiple sources are listed if the term is shared across different standards.

Usage

from datasets import load_dataset

dataset = load_dataset("netrias/cancer_metadata_harmonization")

train = dataset["train"]
validation = dataset["validation"]
id_test = dataset["id_test"]
ood_test = dataset["ood_test"]

print(f"Train Example:\n{train[0]}")
print(f"\nValidation Example:\n{validation[0]}")
print(f"\nIn-Dictionary Test Example:\n{id_test[0]}")
print(f"\nOut-of-Dictionary Test Example:\n{ood_test[0]}")

Citation

If you use this dataset, please cite:

Verbitsky A., Boutet P., Eslami M. (2025). Metadata Harmonization from Biological Datasets with Language Models. bioRxiv. https://doi.org/10.1101/2025.01.15.633281

License

This dataset is released under the Apache License 2.0.