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arXiv · 2311.10443

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

Teresa Zulueta-Coarasa·Florian Jug·Aastha Mathur·Josh Moore·Arrate Muñoz-Barrutia·Liviu Anita·Kola Babalola·Pete Bankhead·Perrine Gilloteaux·Nodar Gogoberidze·Martin Jones·Gerard J. Kleywegt·Paul Korir·Anna Kreshuk·Aybüke Küpcü Yoldaş·Luca Marconato·Kedar Narayan·Nils Norlin·Bugra Oezdemir·Jessica Riesterer·Norman Rzepka·Ugis Sarkans·Beatriz Serrano·Christian Tischer·Virginie Uhlmann·Vladimír Ulman·Matthew Hartley
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Abstract

Artificial Intelligence methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new methods, but access to such data is often hindered by the lack of standards for sharing datasets. We brought together community experts in a workshop to develop 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 positive that the MIFA (Metadata, Incentives, Formats, and Accessibility) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to high quality training data.

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Teresa Zulueta-Coarasa, Florian Jug, Aastha Mathur, Josh Moore, Arrate Muñoz-Barrutia, Liviu Anita, Kola Babalola, Pete Bankhead, Perrine Gilloteaux, Nodar Gogoberidze, Martin Jones, Gerard J. Kleywegt, Paul Korir, Anna Kreshuk, Aybüke Küpcü Yoldaş, Luca Marconato, Kedar Narayan, Nils Norlin, Bugra Oezdemir, Jessica Riesterer, Norman Rzepka, Ugis Sarkans, Beatriz Serrano, Christian Tischer, Virginie Uhlmann, Vladimír Ulman, Matthew Hartley. 2023-11-17. MIFA: Metadata, Incentives, Formats, and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis. https://arxiv.org/abs/2311.10443

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