AndrewNanu-app/Uapornot

Dataset Card for UAP Or Not?

This dataset contains crowd-sourced responses for classifying images as Unidentified Aerial Phenomena (UAP) or providing prosaic explanations. It is designed to gather and analyze user opinions on UAP sightings through an interactive interface.

Dataset Details

Dataset Description

The "UAP or Not?" dataset collects user responses on the likelihood of images being UAPs. Users rank the likelihood on a scale from 0 to 100, and if the likelihood is less than 100%, they provide prosaic explanations through a dropdown menu or a text entry field. This dataset aims to gather diverse opinions and explanations to better understand public perception of UAP sightings.

• Curated by: Andrew Herr
• Funded by: Project Nanu
• Shared by: Andrew Herr
• Language(s) (NLP): English
• License: MIT

Dataset Sources

• Repository: https://huggingface.co/datasets/AndrewNanu-app/Uapornot
• Paper: Not Applicable
• Demo: [Link to your Gradio demo if available]

Uses

Direct Use

This dataset is suitable for research on public perception of UAP sightings, machine learning models for image classification, and analysis of crowd-sourced data on aerial phenomena.

Out-of-Scope Use

The dataset should not be used for making definitive claims about the existence of UAPs or for purposes other than research and analysis of public perception.

Dataset Structure

The dataset consists of the following fields:

• image: URL of the image being classified.
• likelihood: User-provided likelihood of the image being a UAP (0-100 scale).
• classification: User's classification of the image (e.g., UAP, Plane, Meteor, Starlink, Other).
• other_explanation: User-provided explanation if "Other" is selected.

Example Entry

• image: "https://example.com/image1.jpg"
• likelihood: 85
• classification: "Plane"
• other_explanation: ""

Dataset Creation

Curation Rationale

The dataset was created to collect diverse opinions on UAP sightings and to facilitate research on public perception and image classification of aerial phenomena.

Source Data

The images used in this dataset were scraped from the National UFO Reporting Center (NUFORC) database.

Data Collection and Processing

Data was collected through an interactive Gradio interface where users could view images, rank the likelihood of them being UAPs, and provide explanations. The images were scraped from NUFORC and processed to ensure they are suitable for display. Responses were recorded and stored using the Hugging Face datasets library.

Who are the source data producers?

The source data producers are users of the interactive Gradio interface, who voluntarily provided their classifications and explanations.

Annotations

Annotation process

Annotations were collected through the user interface without additional processing or guidelines. Each user's response is considered an annotation.

Who are the annotators?

Annotators are the users who interacted with the Gradio interface to classify the images and provide explanations.

Personal and Sensitive Information

The dataset does not contain personal, sensitive, or private information. All responses are anonymized and do not include user identifiers.

Bias, Risks, and Limitations

The dataset may be biased based on the demographic of the users providing responses. There is also a risk of misclassification due to the subjective nature of the task. Users should be aware that the dataset reflects opinions and not definitive truths.

Recommendations

Users should consider the potential biases and limitations of the dataset when conducting analyses. Cross-referencing with expert reviews and additional datasets is recommended for comprehensive studies.

Citation

BibTeX:

@dataset{uap_or_not_2023,
  author = {Andrew Herr},
  title = {UAP or Not?},
  year = {2023},
  howpublished = {\url{https://huggingface.co/datasets/AndrewNanu-app/Uapornot}},
}