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MIFA : Metadata, Incentives, Formats and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis

Zulueta-Coarasa, Teresa ; Jug, Florian ; Mathur, Aastha ; Moore, Josh ; Muñoz-Barrutia, Arrate ; Anita, Liviu ; Babalola, Kolawole ; Bankhead, Peter ; Gilloteaux, Perrine and Gogoberidze, Nodar , et al. (2025) In Nature Methods 22(11). p.2245-2252
Abstract

Artificial intelligence (AI) methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new algorithms, but access to such data is often hindered by the lack of standards for sharing datasets. We discuss the barriers to sharing annotated image datasets and suggest specific guidelines to improve the reuse of bioimages and annotations for AI applications. These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets. We are sure that the Metadata, Incentives, Formats and Accessibility (MIFA) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to... (More)

Artificial intelligence (AI) methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new algorithms, but access to such data is often hindered by the lack of standards for sharing datasets. We discuss the barriers to sharing annotated image datasets and suggest specific guidelines to improve the reuse of bioimages and annotations for AI applications. These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets. We are sure that the Metadata, Incentives, Formats and Accessibility (MIFA) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to high-quality training and benchmarking data.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Methods
volume
22
issue
11
pages
8 pages
publisher
Nature Publishing Group
external identifiers
  • pmid:40954297
  • scopus:105016494386
ISSN
1548-7091
DOI
10.1038/s41592-025-02835-8
language
English
LU publication?
yes
additional info
Publisher Copyright: © Springer Nature America, Inc. 2025.
id
f5c81c7d-def1-4b50-9dfd-72f13f56ef59
date added to LUP
2026-01-09 17:15:04
date last changed
2026-02-06 20:01:00
@article{f5c81c7d-def1-4b50-9dfd-72f13f56ef59,
  abstract     = {{<p>Artificial intelligence (AI) methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new algorithms, but access to such data is often hindered by the lack of standards for sharing datasets. We discuss the barriers to sharing annotated image datasets and suggest specific guidelines to improve the reuse of bioimages and annotations for AI applications. These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets. We are sure that the Metadata, Incentives, Formats and Accessibility (MIFA) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to high-quality training and benchmarking data.</p>}},
  author       = {{Zulueta-Coarasa, Teresa and Jug, Florian and Mathur, Aastha and Moore, Josh and Muñoz-Barrutia, Arrate and Anita, Liviu and Babalola, Kolawole and Bankhead, Peter and Gilloteaux, Perrine and Gogoberidze, Nodar and Jones, Martin L. and Kleywegt, Gerard J. and Korir, Paul and Kreshuk, Anna and Küpcü Yoldaş, Aybüke and Marconato, Luca and Narayan, Kedar and Norlin, Nils and Oezdemir, Bugra and Riesterer, Jessica L. and Russell, Craig and Rzepka, Norman and Sarkans, Ugis and Serrano-Solano, Beatriz and Tischer, Christian and Uhlmann, Virginie and Ulman, Vladimír and Hartley, Matthew}},
  issn         = {{1548-7091}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{2245--2252}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Methods}},
  title        = {{MIFA : Metadata, Incentives, Formats and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis}},
  url          = {{http://dx.doi.org/10.1038/s41592-025-02835-8}},
  doi          = {{10.1038/s41592-025-02835-8}},
  volume       = {{22}},
  year         = {{2025}},
}