metadata

task_categories:
  - tabular-classification
tags:
  - chemistry
  - climate
size_categories:
  - n<1K
language:
  - en
license: other
license_name: nist
license_link: https://github.com/mahynski/pychemauth/blob/main/LICENSE.md

Summary

This dataset was originally reported in Mahynski et al. (2021) and used in the Mahynski et al. (2022) publication. See these papers for a full description of the dataset's origin and processing. From Mahynski2021:

The multi-entity, long-term Seabird Tissue Archival and Monitoring Project (STAMP) has collected eggs from various avian species throughout the North Pacifc Ocean for over 20 years to create a geospatial and temporal record of environmental conditions. Over 2,500 samples are currently archived at the NIST Biorepository at Hollings Marine Laboratory in Charleston, South Carolina. Longitudinal monitoring efforts of this nature provide invaluable data for assessment of both wildlife and human exposures as these species often consume prey (e.g., fish) similar to, and from sources (e.g., oceanic) comparable to, human populations nearby. In some areas, seabird eggs also comprise a signifcant part of subsistence diets providing nutrition for indigenous peoples. Chemometric profles and related health implications are known to differ across species. Eggs, however, can be diffcult to assign to a species unless the bird is observed on the nest from which the sample was collected due to similar appearance within a genus and sympatric nesting behavior. This represents a large point of uncertainty for both wildlife managers and exposure researchers alike.

Here we have curated analytical data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides, and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the North Pacifc Ocean.

The data here was obtained from github.com/mahynski/stamp-dataset-1999-2010 using the PyChemAuth package.

Here are some summary statistics of the seabirds in the dataset.

Citation

@article{Mahynski2021,
   author = {Nathan A. Mahynski and Jared M. Ragland and Stacy S. Schuur and Rebecca Pugh and Vincent K. Shen},
   doi = {10.6028/jres.126.028},
   journal = {Journal of Research of the National Institute of Standards and Technology},
   title = {Seabird Tissue Archival and Monitoring Project (STAMP) Data from 1999-2010},
   url = {https://dx.doi.org/10.6028/jres.126.028},
   volume = {126},
   number = {126028},
   year = {2021},
}

@article{Mahynski2022,
  title={Building interpretable machine learning models to identify chemometric trends in seabirds of the north pacific ocean},
  author={Nathan A. Mahynski and Jared M. Ragland and Stacy S. Schuur and Vincent K. Shen},
  journal={Environmental Science \& Technology},
  volume={56},
  number={20},
  pages={14361--14374},
  year={2022},
  publisher={ACS Publications}
}

Access

See HuggingFace documentation on loading a dataset from the hub. Briefly, you can access this dataset using the huggingface api like this:

from huggingface_hub import hf_hub_download
import pandas as pd

dataset = pd.read_csv(
    hf_hub_download(
      repo_id="mahynski/stamp2010",
      filename="train.csv",
      repo_type="dataset",
      token="hf_*" # Enter your own token here
  ) 
)

or using datasets:

from datasets import load_dataset

ds = load_dataset(
  "mahynski/stamp2010",
  token="hf_*" # Enter your own token here
)
df = ds['train'].to_pandas()