Published March 28, 2025 | Version 1

SalmoSapro Metadata Catalog: A Cross-Platform Index of Salmonid Images with Saprolegnia Classifications

  • 1. EDMO icon Cardiff University School of Biosciences

Contributors

  • 1. Ogmore Angling Association

Description

This dataset contains structured metadata for salmonid images collected from the publicly accessible online photo-sharing platforms Flickr, iNaturalist, GBIF, and Wikimedia Commons. The collection period spanned December 2023 to February 2024, resulting in a catalogue of fish photograph metadata that has been enriched with manual assessments for visible signs of Saprolegnia infection.

The data set contains metadata for 4,265 images, where 235 have been evaluated to present with visible signs of Saprolegnia spp. and 4,030 have been evaluated to look healthy. 

For each catalogued image, the dataset provides:

  • [source] Original source platform
  • [image_url] Direct URL to access the original image at its source
  • [taxa] Taxonomic classification (based on information from the source platform)
  • [saprolegnia] Binary classification indicating presence/absence of visible Saprolegnia indicators (yes/no)

This metadata repository represents a curated index of passive citizen science, as the original photographs were captured without scientific intent (primarily by recreational anglers and nature enthusiasts) but collectively provide valuable ecological data. All image metadata was compiled through official APIs using systematic keyword and taxonomic-level searches. The search terminology was developed by integrating comprehensive scientific and common salmonid nomenclature from authoritative sources including FishBase, FishTreeOfLife, and NCBI taxonomy databases. This metadata collection serves as a navigational resource for researchers studying fish health and pathogen distribution, allowing them to locate relevant images across multiple platforms while providing standardized classifications of disease presence. It can also support the development of computer vision tools by providing a pre-classified index of images for training. Users of this dataset should respect the original licensing terms of each image when accessing them through the provided URLs.

The data was labelled using LabelBox [1]

[1] Labelbox, "Labelbox," Online, 2025. [Online]. Available: https://labelbox.com

Files

sapro_final_database.csv

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Additional details

Funding

Natural Environment Research Council
ArtiFISHal Intelligence: merging technology and ecology to understand infectious disease dynamics NE/X01049X/1
Natural Environment Research Council
FRESH - NERC Centre for Doctoral Training in Freshwater Biosciences and Sustainability NE/R011524/1

Dates

Collected
2023-12/2024-02
The images described in this data set were downloaded between December 2023 and February 2024

Software

Repository URL
https://github.com/oagn/computer-vision-fish-disease
Programming language
Python , Jupyter Notebook , Shell
Development Status
Active