Merge pull request #1204 from NFDI4BIOIMAGE/git-bob-mod-1x3TnUwFOg

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

Author: haesleinhuepf

resources/nfdi4bioimage.yml

@@ -27130,3 +27130,280 @@ resources:
   url:
   - https://zenodo.org/records/19352622
   - https://doi.org/10.5281/zenodo.19352622
+- authors:
+  - Wetzker, Cornelia
+  - Ahmadi, Mohsen
+  - "Kroo\xDF, Ksenia"
+  - Wendt, Jens
+  - Boissonnet, Tom
+  description: 'The slides are part of a hands-on session that demonstrates the usage
+    of OMERO.figure to create overviews of microscopy images and datasets presented
+    at the Workshop Data Stewardship in Microscopy at the Trends in Microscopy 2025.
+
+    Usage of the material in self learning:
+
+    To be able to follow the hands-on material, find the 3 example datasets of the
+    workshop openly accessible in a public user space of an OMERO instance at the
+    University of Münster via this link: https://omero-tim.gerbi-gmb.de/webclient/?show=dataset-25739
+
+    Alternatively, open the tool omero.figure in this instance directly (https://omero-tim.gerbi-gmb.de/figure/)
+    and add one of the datasets by providing its id: 105986. (see the slides for details)
+
+    Origin of the microscopy dataset:
+
+    The datasets originate from a project dealing with fluorescence lifetime imaging
+    microscopy (FLIM) and its possible application to distinguish spectrally overlapping
+    fluorophores based on their lifetimes. The scientific context and further
+    processing of the image datasets are described in the following publication: https://doi.org/10.1111/jmi.70036
+
+    The complete bioimage dataset including experimental, microscopy and image analysis
+    metadata can be found on the BioImage Archive: https://www.ebi.ac.uk/biostudies/bioimages/studies/S-BIAD1967'
+  license: cc-by-4.0
+  name: '[TiM2025] Hands-on: Creating Bio-image Overviews with OMERO.figure'
+  num_downloads: 0
+  publication_date: '2026-06-09'
+  submission_date: '2026-06-09T13:45:54.139699'
+  url:
+  - https://zenodo.org/records/20610539
+  - https://doi.org/10.5281/zenodo.20610539
+- authors:
+  - Moore, Josh
+  - Schmidt, Christian
+  - Haase, Robert
+  - Mallm, Jan-Philipp
+  - Fortmann-Grote, Carsten
+  - Figge, Thilo
+  - Tischer, Christian
+  - Sun, Yi
+  - Zobel, Thomas
+  - Wendt, Jens
+  - "Gr\xFCning, Bj\xF6rn"
+  - Kunis, Susanne
+  - Blank-Burian, Markus
+  - Trivedi, Ami
+  - Hanne, Janina
+  - von Suchodoletz, Dirk
+  - Scherle, Michael
+  - Massei, Riccardo
+  - Wetzker, Cornelia
+  - "M\xFCller, Maximilian"
+  - Baldenius, Marie
+  - Mohr, Inga
+  - Fuchs, Vanessa
+  - Gottschall, Tobias
+  - Bortolomeazzi, Michele
+  - Gerst, Ruman
+  - Ahmadi, Mohsen
+  - Chen, Jianxu
+  - Becker, Markus
+  - Ferrando-May, Elisa
+  - Weidtkamp-Peters, Stefanie
+  description: 'Interim Progress Report of the Consortium NFDI4BIOIMAGEPart 1 published
+    at: https://www.dfg.de/en/research-funding/funding-initiative/nfdi/progress-reportsPart
+    2 published here.
+
+     
+
+    Biological imaging is a core pillar of modern life science, enabling quantitative
+    insight across scales and disciplines, from molecular biology to medicine. Increasingly,
+    imaging is combined with other data modalities such as genomics and proteomics,
+    positioning bioimaging at the heart of phenomics and integrative research. At
+    the same time, bioimaging experiments are among the largest and most heterogeneous
+    produced in academia, often surpassing terabyte scale. Without shared standards,
+    scalable infrastructure, and coordinated community practices, much of this data
+    risks remaining siloed or non-reusable, limiting its scientific value for the
+    wider research community. NFDI4BIOIMAGE was established to address these
+    challenges by embedding the German bioimaging community within a strong international
+    ecosystem and contributing to long-standing global goals around data acquisition,
+    management, discovery, and publication. Three years into its five-year funding
+    period, NFDI4BIOIMAGE has become a visible and trusted actor in shaping how bioimaging
+    data are standardized, shared, analyzed, and sustained, both nationally and internationally[1].
+    At its inception, the consortium defined four closely linked objectives, spanning
+    the full bioimaging data lifecycle and aligning national efforts with international
+    developments (Figure 1).
+
+    A central objective of NFDI4BIOIMAGE has been to champion open, community-driven
+    standards (Obj. 1) that enable data to be reused across tools, institutions, and
+    scientific domains. The consortium has led the development and international adoption
+    of a Next-Generation File Format (NGFF) through a Request for Comments (RFC) process.
+    This work directly addresses the needs of modern, cloud-scale, and multimodal
+    imaging and has attracted sustained engagement from global partners, including
+    follow-on funding from international sources such as Wellcome and Biohub. NGFF,
+    however, goes beyond a file format, by enabling systematic extension in other
+    ecosystems, like the emerging SpatialData standard for the specific needs of spatially
+    resolved omics. This serves as a blueprint for domain-specific specialization
+    from a shared core standard. In collaboration with the BioImage Archive (BIA)
+    at EBI, the consortium is contributing to interoperable metadata specifications
+    that move bioimaging closer to FAIR Digital Objects (FDOs), or “FAIR Image
+    Objects” (FAIR-IO). Additional contributions include promotion of REMBI
+    (Recommended Metadata for Biological Images) as a de facto metadata standard,
+    RO-Crate–based packaging approaches, and expanding our data ambassador model
+    into FAIR data champions who drive community adoption.
+
+    To make standards usable in practice, NFDI4BIOIMAGE has invested heavily in scalable,
+    interoperable infrastructure (Obj. 2) supporting both national and international
+    workflows. This includes cloud-ready analysis environments based on Jupyter, object
+    storage, Desktop-as-a-Service (DaaS) and workflow platforms such as Galaxy, enabling
+    reproducible analysis of large imaging datasets across infrastructures. The consortium
+    has supported the migration of major international resources, including the Image
+    Data Resource (IDR), to scalable cloud-based access models and has worked closely
+    with EMBL-EBI to convert BioImage Archive holdings into REMBI-annotated NGFFs,
+    namely OME-Zarr, substantially improving online accessibility and reuse.
+
+    At the software level, NFDI4BIOIMAGE has strengthened tools for maximizing reproducible
+    bioimage analysis (Obj. 3), such as Galaxy and JIPipe, adding features including
+    RO-Crate packaging, OME-Zarr support, and OMERO integration to bridge experimental
+    analysis pipelines with FAIR data publication. The BioImage ANalysis Desktop (BAND)
+    has served as a key transitional DaaS platform, bringing users’ experience
+    closer to their large-scale imaging data in the cloud while maintaining an interactive,
+    reproducible computational environment, which is particularly effective for training
+    and lowering barriers to advanced analysis. The consortium has also engaged with
+    emerging AI ecosystems like Hugging Face, aligning bioimaging workflows with broader
+    developments in machine learning and reproducible research. In parallel, the consortium
+    has supported local data stewardship and storage solutions at multiple German
+    institutions and the operation of federated OMERO services, ensuring national
+    capacity grows in step with international alignment.
+
+    A defining strength of NFDI4BIOIMAGE is its emphasis on capacitating researchers
+    through training and data stewardship (Obj. 4). Over the past three years, the
+    consortium has delivered a broad program of training and capacity building, including
+    institutional workshops, national courses, and contributing to major international
+    conferences, and enhanced access to open educational resources for bioimaging
+    RDM. Flagship initiatives such as RDM4mic and I3D:bio have significantly raised
+    awareness and competence around research data management in bioimaging by giving
+    the community a platform to actively engage. NFDI4BIOIMAGE has, furthermore, helped
+    professionalize data stewardship roles through helpdesks and cross-consortia collaboration,
+    supported data submission to the BioImage Archive, and improved discoverability
+    through catalogs of tools, services, and use cases integrated into institutional
+    research structures.
+
+    In addition, NFDI4BIOIMAGE contributes actively beyond its consortium. The speaker
+    has chaired the NFDI Konsortialversammlung while members participate broadly in
+    relevant NFDI Sections, notably those focused on metadata (including ontologies,
+    search, and knowledge graphs) and on common infrastructure and data integration.
+    Internationally, consortium members contribute to ISO standardization, provide
+    leadership within the Open Microscopy Environment (OME), and represent bioimaging
+    interests in the European Open Science Cloud (EOSC). Engagement in initiatives
+    such as IO-FAST and foundingGIDE, together with close ties to Global BioImaging,
+    further amplify Germany’s visibility in the global imaging landscape. For
+    the final two years of funding, NFDI4BIOIMAGE’s priorities include the formal
+    standardization of widely adopted practices for bioimage data, establishment of
+    a national OMERO framework in coordination with de.NBI (underpinned by an MoU),
+    and the development of sustainable operational models for bioimaging data services.
+    While challenges remain, particularly around long-term sustainability and scaling,
+    the consortium has laid a robust foundation. By combining standards, infrastructure,
+    tools, and people, NFDI4BIOIMAGE has positioned Germany as a central contributor
+    to a FAIR, reproducible, globally connected bioimaging ecosystem.
+
+
+
+
+    [1] https://youtu.be/7nj2BkRJ8Q0
+
+
+    '
+  license: cc-by-4.0
+  name: NFDI4BIOIMAGE Interim Progress Report (03/2023 - 02/2026)
+  num_downloads: 16
+  publication_date: '2026-06-02'
+  submission_date: '2026-06-09T13:45:54.584477'
+  url:
+  - https://zenodo.org/records/20509378
+  - https://doi.org/10.5281/zenodo.20509378
+- authors:
+  - Haase, Robert
+  description: 'In  this presentation we learn  about the impact of generative
+    artificial intelligence (AI), and in particular large language models (LLMs),
+    on the field of bio image analysis. We dive deeper into data analysis code-generation
+    and AI systems built around LLMs integrating code generation in our workflows
+    conveniently:
+
+
+    bia-bob
+
+    git-bob
+
+    sand-bob
+
+
+    Finally, we take a look at how these systems can be used on sovereign infrastructure
+    to support privacy in a scientific context.'
+  license: cc-by-4.0
+  name: How Generative Artificial Intelligence impacts Bio-image Data Science
+  num_downloads: 182
+  publication_date: '2026-06-02'
+  submission_date: '2026-06-09T13:45:55.083802'
+  url:
+  - https://zenodo.org/records/20512957
+  - https://doi.org/10.5281/zenodo.20512957
+- authors:
+  - Moore, Josh
+  description: '40 Minute talk presented to the BINA Insights and Educational Tools
+    from Industry Series
+
+    https://www.bioimagingnorthamerica.org/events/insights-and-educational-tools-from-industry-series-registration/'
+  license: cc-by-4.0
+  name: '[BINA] Understanding the Standardization Runway of OME-Zarr'
+  num_downloads: 49
+  publication_date: '2026-05-20'
+  submission_date: '2026-06-09T13:45:55.545974'
+  url:
+  - https://zenodo.org/records/20275730
+  - https://doi.org/10.5281/zenodo.20275730
+- authors:
+  - Kemmer, Isabel
+  - Euro-BioImaging ERIC
+  description: 'Abstract: Euro-BioImaging Image Data Services includes the FAIR Data
+    Toolkit to support its network of Nodes and their research communities in implementing
+    robust bioimage data handling. This toolkit includes customizable data management
+    plan templates, metadata & deposition guides, repository decision trees and
+    a collection of training resources and consultation opportunities. All of these
+    are designed to provide guidance around the entire bioimage data lifecycle, from
+    acquisition to reuse. Beneath the surface of these resources, OME standards and
+    tools provide the technical foundations for interoperability. Whether it’s
+    OME metadata standards, Bio-Formats, OMERO, OME-Zarr, or the IDR, all of them
+    are woven into the toolkit and shape our trainings and consultations. To enable
+    broad adoption of OME-Zarr, we’re also creating open-source tools that streamline
+    conversion and work with it. Through this OME integration, Euro-BioImaging turns
+    FAIR community solutions into everyday practice by equipping Nodes with ready-to-use
+    resources for their staff and researchers. Nodes adapt and distribute the toolkit
+    locally, amplifying standardized, reproducible, and interoperable data handling
+    across Europe’s bioimaging community.
+
+    Note: this digital version of the poster was updated on 2026-05-27 with the latest
+    numbers for Euro-BioImaging facilities and Image Data Community Days and is therefore
+    slightly different than the one presented at the meeting.'
+  license: cc-by-4.0
+  name: '[OME2026] Poster:Putting FAIR Principles into Action - Euro-BioImaging''s
+    FAIR Data Toolkit'
+  num_downloads: 29
+  publication_date: '2026-04-28'
+  submission_date: '2026-06-09T13:46:20.979002'
+  url:
+  - https://zenodo.org/records/20152438
+  - https://doi.org/10.5281/zenodo.20152438
+- authors:
+  - Theart, Rensu
+  - Levet, Florian
+  - Hernandez-Herrera
+  - Leterrier, Christophe
+  - de la Ballina, Laura R
+  description: 'Raw, processed and annotated images associated with the manuscript
+    "Presynaptic Actin Nanostructures: A Reproducibility Case Study".
+
+    This work is part of an initiative of the Global BioImage Analysts'' Society (GloBIAS)
+    to assess reproducibility of published bioimage analysis workflows.
+
+    We present our attempt to reproduce Figure 7 of the article Presynapses contain
+    distinct actin nanostructures. J Cell Biol 2 October 2023; 222 (10): e202208110.
+    doi: https://doi.org/10.1083/jcb.202208110. Original images and annotations
+    were kindly provided by their authors.'
+  license: cc-by-4.0
+  name: 'Sample image data and annotations associated to Presynaptic Actin Nanostructures:
+    A Reproducibility Case Study'
+  num_downloads: 27
+  publication_date: '2026-05-26'
+  submission_date: '2026-06-09T13:47:01.007353'
+  url:
+  - https://zenodo.org/records/20386408
+  - https://doi.org/10.5281/zenodo.20386408