license: other
license_name: various-open-licenses
license_link: https://www.flickr.com/commons/usage/
tags:
- flickr
- flickr-commons
- data-lifeboat
size_categories:
- 1K<n<10K
language:
- en
task_categories:
- image-classification
- image-to-text
- text-retrieval
- visual-question-answering
pretty_name: Flickr Commons 1K Collection
Flickr Commons 1K Collection
Dataset Description
This dataset is a Flickr Data Lifeboat converted to a machine learning ready/ Hugging Face datasets compatible format. Data Lifeboats are digital preservation archives created by the Flickr Foundation to ensure long-term access to meaningful collections of Flickr photos and their rich community metadata.
What is a Data Lifeboat?
Data Lifeboats are self-contained archives designed to preserve not just images, but the social and cultural context that makes them meaningful:
- Complete photo metadata and community interactions
- User-generated tags, descriptions, and comments
- Attribution and licensing information
- No external dependencies for long-term preservation
Collection Details:
- Original Collection ID:
COMMONS_1K_2025
- Created: 2025-01-16 17:03:19.752253
- Curator: the Flickr Foundation
Purpose
The Flickr Foundation produced this special collection for release in January 2025. It showcases some of the most popular photography across the groundbreaking Flickr Commons program. We hope you enjoy it!
Related Datasets
Raw Data Lifeboat Version
This dataset also has a raw, self-contained archive version that preserves the original Data Lifeboat format:
🗂️ Raw Archive: davanstrien/flickr-lifeboat-commons-1k-2025-raw
The raw version includes:
- Built-in web viewer (
viewer/index.html
) - Complete original file structure
- Self-contained archive (no external dependencies)
- Ideal for digital preservation and archival research
Choose the raw version if you need the complete preservation format or want to use the built-in viewer.
Dataset Statistics
Collection Overview
- Total Photos: 1,000
- Total Tags: 13,356
- Total Comments: 24,831
- Contributors: 20,281
- Date Range: 2008-01-08 to 2025-01-04
- Photos with Location: 216 (21.6%)
License Distribution
- nkcr: 1000 photos
Format Distribution
- jpg: 984 photos
- png: 16 photos
Engagement Metrics
- Average Views: 101,857 (max: 10,186,629)
- Average Favorites: 247 (max: 29,270)
- Average Comments: 0.0 (max: 0)
Top Contributing Institutions/Users
- NASA on The Commons: 15 photos
- LlGC ~ NLW: 14 photos
- IWM Collections: 13 photos
- Museum of Hartlepool: 13 photos
- National Library of Australia Commons: 13 photos
Dataset Structure
Field Descriptions
Field | Type | Description |
---|---|---|
image |
Image | Original resolution photo |
thumbnail |
Image | Thumbnail version |
photo_id |
string | Unique Flickr identifier |
secret |
string | Flickr URL construction parameter (enables direct access to public domain photos) |
url |
string | Original Flickr URL |
title |
string | Photo title |
description |
string | Photo description |
uploader_username |
string | Username of uploader |
license_label |
string | Human-readable license |
date_taken |
string | When photo was captured |
date_uploaded |
timestamp | When uploaded to Flickr |
latitude/longitude |
float | GPS coordinates (if available) |
count_views/faves/comments |
int | Community engagement metrics |
tags |
list[string] | User-generated tags |
comments |
list[dict] | Full comment threads with metadata |
Note on secret
field: This is a Flickr-specific parameter required for constructing direct image URLs. While normally sensitive, it's appropriate to include here because all photos are public domain and this enables the self-contained nature of Data Lifeboat archives.
Usage
Basic Loading
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("your-username/dataset-name")
# Access images and metadata
for example in dataset["train"]:
image = example["image"]
title = example["title"]
tags = example["tags"]
comments = example["comments"]
Research Applications
This dataset is suitable for:
- Computer Vision: Image classification, scene understanding, visual content analysis
- Vision-Language: Image-to-text generation, visual question answering
- Digital Humanities: Cultural heritage analysis, community interaction studies
- Information Retrieval: Text-based image search, tag prediction, metadata analysis
- Social Media Research: Community engagement patterns, collaborative annotation
Working with Comments and Tags
# Analyze community engagement
for example in dataset["train"]:
photo_id = example["photo_id"]
num_comments = len(example["comments"])
tags = example["tags"]
print(f"Photo {photo_id}: {num_comments} comments, {len(tags)} tags")
Source Data
Data Collection
This collection originates from Flickr's Commons program, which partners with cultural heritage institutions to share photographs with no known copyright restrictions. Photos are selected based on cultural significance, community engagement, and preservation value.
Community Annotations
All metadata reflects authentic community interaction:
- Tags: User-generated keywords and descriptions
- Comments: Community discussions and reactions
- Engagement metrics: Real view counts, favorites, and interactions
Licensing and Ethics
License Information
Photos in this collection have open licenses enabling reuse:
- Most common: "No known copyright restrictions"
- Also includes: Creative Commons licenses (CC0, CC BY, etc.)
- See
license_label
andlicense_url
fields for specific licensing per image
Ethical Considerations
- Historical Context: Some photos may depict people, places, or events from historical periods
- Community Content: Comments and tags reflect community perspectives at time of creation
- Attribution: Original photographers and institutions are preserved in metadata
- Public Domain: All content was publicly accessible on Flickr under open licenses
Citation
@misc{commons_1k_2025},
title = {Flickr Commons 1K Collection},
author = {the Flickr Foundation},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/[dataset-url]},
note = {Flickr Data Lifeboat digital preservation format}
}
Additional Information
Future Considerations
The photos contained in this collection come to you with no known copyright restrictions. You are welcome to use them as you wish. Please consider giving credit to the cultural institutions who have shared these photos with us.
About Data Lifeboats
Learn more about the Data Lifeboat initiative:
Dataset Maintenance
This dataset was created using the Flickr Foundation's Data Lifeboat format and converted to Hugging Face using automated tools that preserve all original metadata and community context.