Merge pull request #790 from NFDI4BIOIMAGE/git-bob-mod-UfraAMgqRD

Add content from communities: nfdi4bioimage, gerbi, euro-bioimaging, neubias, bio-formats, globias, rdm4mic

Author: haesleinhuepf

resources/nfdi4bioimage.yml

@@ -14594,3 +14594,49 @@ resources:
   url:
   - https://zenodo.org/records/15579371
   - https://doi.org/10.5281/zenodo.15579371
+- authors:
+  - Moore, Josh
+  description: 'Presented at https://www.embl.org/about/info/course-and-conference-office/events/elmi2025/
+
+     
+
+    Abstract
+
+    For over 20 years, the Open Microscopy Environment (OME) has developed tools and
+    specifications to support bioimaging data sharing. Technologies such as Bio-Formats,
+    OMERO, and OME-TIFF have helped researchers manage the growing size, complexity,
+    and acquisition rates of imaging datasets. However, with increasing mandates for
+    research data management, such as the Nelson memo in the United States, and the
+    shift toward cloud-native workflows, the bioimaging community faces new challenges
+    in ensuring scalable and FAIR data infrastructure.
+
+    In 2024, following expanding community engagement, the focus of the Next-Generation
+    File Format (NGFF) community was on building consensus around a Request for Comments
+    (RFC) process. This collaborative effort has laid the foundation for future refinements
+    and wider adoption. In parallel, we hosted the “OME2024 NGFF Challenge,"
+    bringing together over the course of just four months hundreds of terabytes of
+    data in a first prototype of federated image hosting, showcasing the power of
+    OME-Zarr for handling large-scale, distributed datasets.
+
+    In 2025, we are set to take a major step toward a stable FAIR solution with OME-Zarr
+    1.0. This milestone marks a crucial phase towards an international standard, providing
+    an open, cloud-optimized, and scalable solution for handling terabyte- and petabyte-scale
+    imaging data. The 1.0 release will introduce long-awaited transforms, enabling
+    robust support for multimodal datasets, followed by collections and an extensibility
+    mechanism to accommodate evolving scientific needs. These additions emphasize
+    a solid foundation on which future capabilities can be built while providing the
+    stability needed for broader adoption of the format. This presentation will outline
+    the path to 1.0, including community-driven refinements, vendor engagement to
+    ensure complete metadata representation, and alignment with global bioimaging
+    initiatives. As imaging data continues to grow in scale and complexity, consensus-driven
+    evolution of infrastructure will be key to ensuring a truly FAIR future for bioimaging.
+
+     '
+  license: cc-by-4.0
+  name: '[ELMI2025] The Road to OME-Zarr 1.0'
+  num_downloads: 74
+  publication_date: '2025-06-05'
+  submission_date: '2025-06-10T11:20:53.889968'
+  url:
+  - https://zenodo.org/records/15597856
+  - https://doi.org/10.5281/zenodo.15597856