Image data interoperability with OME-NGFF, RO-Crate and linked data

Global image data sharing is an important long term goal, but requires practical mechanisms for enabling cross-compatibility on which we can build. The presentation was delivered by Matthew Hartley, Team Leader at BioImage Archive, EMBL European Bioinformatics Institute, UK, during the foundingGIDE Community Meeting in Okazaki, Japan (31 October–01 November 2024). foundingGIDE: founding a Global Imaging Data Ecosystem is a EU Horizon-funded project between Euro-BioImaging ERIC, EMBL, Consiglio Nazionale delle Ricerche (Italy), German BioImaging, Global BioImaging, RIKEN (Japan), Microscopy Australia and Australian National Imaging Facility. More information on the project at: https://founding-gide.eurobioimaging.eu

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-11
DOI
https://doi.org/10.5281/zenodo.14396165
Primary Topic
Cell Image Analysis Techniques
Type
article
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article

Image data interoperability with OME-NGFF, RO-Crate and linked data

Zenodo (CERN European Organization for Nuclear Research)
Cell Image Analysis Techniques
article

Image data interoperability with OME-NGFF, RO-Crate and linked data

article en

Abstract

Global image data sharing is an important long term goal, but requires practical mechanisms for enabling cross-compatibility on which we can build. The presentation was delivered by Matthew Hartley, Team Leader at BioImage Archive, EMBL European Bioinformatics Institute, UK, during the foundingGIDE Community Meeting in Okazaki, Japan (31 October–01 November 2024). foundingGIDE: founding a Global Imaging Data Ecosystem is a EU Horizon-funded project between Euro-BioImaging ERIC, EMBL, Consiglio Nazionale delle Ricerche (Italy), German BioImaging, Global BioImaging, RIKEN (Japan), Microscopy Australia and Australian National Imaging Facility. More information on the project at: https://founding-gide.eurobioimaging.eu

Zenodo (CERN European Organization for Nuclear Research)
European Bioinformatics Institute (GB)
Openalex Percentile: Top 47%
Cell Image Analysis Techniques
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