metadata

annotations_creators:
  - found
language:
  - en
language_creators:
  - found
license:
  - unknown
multilinguality:
  - monolingual
pretty_name: scientific_lay_summarisation
size_categories:
  - 10K<n<100K
  - 1K<n<10K
source_datasets:
  - original
tags:
  - scientific papers
  - lay summarization
  - PLOS
  - eLife
task_categories:
  - summarization
task_ids: []

Dataset Card for "scientific_lay_summarisation"

Dataset Summary

This repository contains the PLOS and eLife datasets, introduced in the EMNLP 2022 paper "Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature " .

Each dataset contains full biomedical research articles paired with expert-written lay summaries (i.e., non-technical summaries). PLOS articles are derived from various journals published by the Public Library of Science (PLOS), whereas eLife articles are derived from the eLife journal. More details/anlaysis on the content of each dataset are provided in the paper.

Supported Tasks and Leaderboards

Papers with code - PLOS and eLife.

Languages

English

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

"Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature"
Tomas Goldsack, Zhihao Zhang, Chenghua Lin, Carolina Scarton
EMNLP 2022

Contributions

Thanks to @TGoldsack1 for adding this dataset.