metadata

pretty_name: Scientific Figures, Captions and Context
task_categories:
  - visual-question-answering
  - document-question-answering

Dataset Card for Scientific Figures, Captions, and Context

A novel vision-language dataset of scientific figures taken directly from research papers. We scraped approximately ~150k papers, with about ~690k figures total. We extracted each figure's caption and label from the paper. In addition, we searched through each paper to find references of each figure and included the surrounding text as 'context' for this figure.

All figures were taken from arXiv research papers.

Fig. 6. Accuracy of sample from current (1st) F-MNIST class

Figure 3: Problem representation visualization by T- SNE. Our model with A&D improves the problem rep- resentation learning, which groups analogical problems close and separates non-analogical problems.

Usage

The merged.json file is a mapping between the figure's filename as stored in the repository and its caption, label, and context. To use, you must extract the parts located under dataset/figures/ and keep the raw images in the same directory so that they match the image_filename fields. The images are named in the format -

where paper id is the id given by arXiv and figure name is the name of the figure as given in the raw format of each paper.

Contributors

Yousef Gomaa (@yousefg-codes) and Mohamed Awadalla (@mawadalla)

Dataset Description

Paper:

Dataset Summary

This dataset includes ~690,000 figures from ~150,000 scientific papers taken from arXiv papers. Each object in the json file is a single research paper with a list of figures each with their caption and surrounding context.

Category	Count
Figure	690883
Paper	152504

Languages

The data is in english.

Data Instances

An example of an object in the merged.json file:

{
  [
    {
      'image_filename': 'dataset/figures/example.png' (or .eps or .pdf or other type),
      'label': 'fig_example',
      'caption': 'an example caption for this figure',
      'context': ['example context where this figure was referenced', 'up to 600 characters']
    },
  ...
  ]
}

Dataset Creation

We utilized the bulk access of arXiv's papers.

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]

Citation Information

coming soon