Nfdi4bioimage (80)#
A Cloud-Optimized Storage for Interactive Access of Large Arrays#
Josh Moore, Susanne Kunis
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Content type: Publication, Conference Abstract
A journey to FAIR microscopy data#
Stefanie Weidtkamp-Peters, Janina Hanne, Christian Schmidt
Published 2023-05-03
Licensed CC-BY-4.0
Oral presentation, 32nd MoMAN “From Molecules to Man” Seminar, Ulm, online. Monday February 6th, 2023
Abstract:
Research data management is essential in nowadays research, and one of the big opportunities to accelerate collaborative and innovative scientific projects. To achieve this goal, all our data needs to be FAIR (findable, accessible, interoperable, reproducible). For data acquired on microscopes, however, a common ground for FAIR data sharing is still to be established. Plenty of work on file formats, data bases, and training needs to be performed to highlight the value of data sharing and exploit its potential for bioimaging data.
In this presentation, Stefanie Weidtkamp-Peters will introduce the challenges for bioimaging data management, and the necessary steps to achieve data FAIRification. German BioImaging - GMB e.V., together with other institutions, contributes to this endeavor. Janina Hanne will present how the network of imaging core facilities, research groups and industry partners is key to the German bioimaging community’s aligned collaboration toward FAIR bioimaging data. These activities have paved the way for two data management initiatives in Germany: I3D:bio (Information Infrastructure for BioImage Data) and NFDI4BIOIMAGE, a consortium of the National Research Data Infrastructure. Christian Schmidt will introduce the goals and measures of these initiatives to the benefit of imaging scientist’s work and everyday practice.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
Accessible Interactive Spatial-Omics Data Visualizations with Vitessce and OMERO#
Bortolomeazzi Michele
Published 2025-06-30
Licensed CC-BY-4.0
OMERO is the most used research data management system (RDM) in the bioimaging domain, and has been adopted as a centralized RDM solution by several academic and research institutions. A main reason for this is the ability to directly view and annotate images from a web-based interface. However, this feature of OMERO is currently underpowered for the visualization of very large or multimodal datasets. These datasets, are becoming a more and more common foundation for biological and biomedical studies, due to the recent developments in imaging, and sequencing technologies which enabled their application to spatial-omics. In order to begin to provide this multimodal-data capability to OMERO, we developed omero-vitessce (NFDI4BIOIMAGE/omero-vitessce), a new OMERO.web plugin for viewing data stored in OMERO with the Vitessce (http://vitessce.io/) multimodal data viewer. omero-vitessce can be installed as an OMERO.web plugin with PiPy (https://pypi.org/project/omero-vitessce/), and allows users to set up interactive visualizations of their images of cells and tissues through interactive plots which are directly linked to the image. This enables the visual exploration of bioimage-analysis results and of multimodal data such as those generated through spatial-omics experiments. The data visualization is highly customizable and can be configured not only through custom configuration files, but also with the graphical interface provided by the plugin, thus making omero-vitessce a highly user-friendly solution for multimodal data viewing. most biological datasets. We plan to extend the interoperability of omero-vitessce with the OME-NGFF and SpatialData file formats to leverage the efficiency of these cloud optimized formats.
Tags: Nfdi4Bioimage, OMERO, Include In Dalia
Angebote der NFDI für die Forschung im Bereich Zoologie#
Birgitta König-Ries, Robert Haase, Daniel Nüst, Konrad Förstner, Judith Sophie Engel
Published 2024-12-04
Licensed CC-BY-4.0
In diesem Slidedeck geben wir einen Einblick in Angebote und Dienste der Nationalen Forschungsdaten Infrastruktur (NFDI), die Relevant für die Zoologie und angrenzende Disziplinen relevant sein könnten.
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
BHG2023-OMERO-ARC#
Andrea Schrader, Michele Bortolomeazzi, Niraj Kandpal, Torsten Stöter, Kevin Schneider, Peter Zentis, Josh Moore, Jeam-Marie Burel, Tom Boissonnet
Licensed CC-BY-4.0
Repository for documentation during the 2nd de.NBI BioHackathon Germany - 11.-15.12.2023 - OMERO-ARC project (in short: BHG2023-OMERO-ARC)
Tags: Nfdi4Bioimage, Bioinformatics, OMERO, Exclude From Dalia
Content type: Github Repository
Bio-Image Data Strudel for Workshop on Research Data Management in TU Dresden Core Facilities#
Cornelia Wetzker
Published 2023-11-08
Licensed CC-BY-4.0
This presentation gives a short outline of the complexity of data and metadata in the bioimaging universe. It introduces NFDI4BIOIMAGE as a newly formed consortium as part of the German ‘Nationale Forschungsdateninfrastruktur’ (NFDI) and its goals and tools for data management including its current members on TU Dresden campus.
Tags: Research Data Management, Nfdi4Bioimage, Include In Dalia
Content type: Slides
Bio-image Data Science Lectures 2025 @ Uni Leipzig / ScaDS.AI#
Robert Haase
Published 2025-07-10
Licensed CC-BY-4.0
These are the PPTx training resources for Students at Uni Leipzig who want to dive into bio-image data science with Python. The material will develop here and in the corresponding github repository between April and July 2025.
Tags: Nfdi4Bioimage, Bioimage Analysis, Artificial Intelligence, Exclude From Dalia
Bioimaging workflow based on OMERO, eLabFTW, and Adamant for integrating images with multimodal metadata#
Mohsen Ahmadi, Robert Wagner, Sander Bekeschus, Becker, Markus M.
Published 2025-07-29
Licensed CC-BY-4.0
This research data management workflow for bioimaging is designed to bridge the gap between image metadata and experimental / process metadata. By linking images and microscopy-related metadata with broader experimental records, the workflow particularly supports the adoption of the FAIR (Findable, Accessible, Interoperable, Reusable) data principles in interdisciplinary fields where bioimaging is used to analyse treated samples requiring multimodal metadata. A Jupyter Notebook guides the user through the metadata level, data handling level, and data processing level and connects various software components in a modular manner. On the metadata level, microscope-specific metadata are captured using the Micro-Meta App and stored as reusable digital assets. Adamant provides a user interface to collect and process schema-based metadata related to the experiment / treatment procedure. Structured imaging and process metadata are attached to the complete experiment description in eLabFTW. On the data handling level, OMERO serves as the central platform for storing and managing microscopy images together with their metadata retrieved from eLabFTW (workflow with ELN) or directly from JSON files (workflow without ELN). On the data processing level, OMERO supports both automated and manual image analysis either directly via the Jupyter Notebook or FIJI. Due to the modularity of the workflow, the integrated tools can be substituted with equivalent systems based on institutional / user requirements. Whether in teaching or research settings, this workflow supports high-throughput, reproducible imaging workflows, ensuring that data, metadata, and analysis steps remain transparent, interoperable, and reusable across diverse bioimage analysis platforms.
Tags: Nfdi4Bioimage, Exclude From Dalia
Building FAIR image analysis pipelines for high-content-screening (HCS) data using Galaxy#
Riccardo Massei, Matthias Bernt, Leonid Kostrykin, Jan Bumberger
Published 2024-05-14
Licensed MIT
Imaging plays a crucial role across various scientific disciplines, particularly in life sciences. However, image data often proves complex, and the volume of images requiring analysis is steadily increasing, especially in high-content screening (HCS) experiments involving cell lines or other organisms. Specifically, analysis pipelines must align to the FAIR principles, ensuring they are reusable and interchangeable across different domains
Tags: Nfdi4Bioimage, Include In Dalia
Building a National Research Data Infrastructure#
for Microscopy and BioImage Analysis
Josh Moore
Published 2025-06-30
Licensed CC-BY-4.0
Presentation for the BioImagingUK Meeting taking place from 1200 - 1500 BST on Monday 30 June 2025 at mmc2025 https://www.mmc-series.org.uk/meetings-features/bioimaginguk-meeting.html This pre-congress meeting provides an opportunity for the UK Bioimaging community to discuss priorities and strategies in national infrastructure, technology development, training, careers and ways to share knowledge across different disciplines. The session will consist of short talks from members of the BioImagingUK community and industrial/institute collaboration partners to update on progress, new opportunities and initiatives. There will be interactive Q+A sessions to encourage discussion and enable emerging priorities and ideas to be highlighted.
Tags: Nfdi4Bioimage, Include In Dalia
Challenges and opportunities for bio-image analysis core-facilities#
Robert Haase
Licensed CC-BY-4.0
Tags: Research Data Management, Bioimage Analysis, Nfdi4Bioimage, Include In Dalia
Content type: Slides
Cloud-Based Virtual Desktops for Reproducible Research#
Yi Sun, Christian Tischer, Kelleher, Harry Alexander, Jean-Karim Heriche
Published 2025-09-10
Licensed CC-BY-4.0
Reproducing computing environments become increasingly challenging in research, especially when compute-intensive scientific workflows require specialised software stacks, specialized hardware (e.g. GPUs), and interactive analysis tools. While traditional high-performance computing (HPC) systems offer scalable resources for batch processing, they don’t easily support interactive workflows. On the other hand, workstations have fixed resources and face workflow deployment challenges because conflicts can occur when multiple tools and dependencies are deployed into the same environment. To address these limitations, we present cloud-based virtual desktop platforms, built on the desktop-as-a-service (DaaS) model, using a containerised, cloud-native approach. Our platforms offer on-demand, customized desktop environments accessible from any web browser, with dynamic allocation of CPU, memory, and GPU resources for efficient utilization of resources. We introduce two types of virtual desktops: BAND, built on top of a Slurm scheduler and BARD, using Kubernetes. In both cases, containerization ensures consistent and reproducible environments across sessions and pre-installed software improves accessibility for researchers. Deployment and system administration are also simplified through the use of orchestration and automation tools. Our virtual desktop platforms are particularly valuable for bioimage analysis, which requires complex workflows involving high interactivity, multiple software and GPU acceleration. By combining containerization and cloud-native services, BAND and BARD offer a scalable and sustainable model for delivering interactive, reproducible research environments.
Tags: Nfdi4Bioimage, Exclude From Dalia
Cloud-Native Formats Enable Federated Repositories at Peta-Scale#
Josh Moore
Published 2025-09-27
Licensed CC-BY-4.0
Poster presentation for the abstract “Enabling Peta-Scale Federated Repositories through Cloud-Native Formats: Lessons from a fast-paced challenge in the bioimaging community” submitted to 2nd Conference on Research Data Infrastructure (CoRDI) 2025
Tags: Nfdi4Bioimage, Include In Dalia
Collaborative Working and Version Control with git[hub]#
Robert Haase
Published 2024-01-10
Licensed CC-BY-4.0
This slide deck introduces the version control tool git, related terminology and the Github Desktop app for managing files in Git[hub] repositories. We furthermore dive into:* Working with repositories* Collaborative with others* Github-Zenodo integration* Github pages* Artificial Intelligence answering Github Issues
Tags: Nfdi4Bioimage, Globias, Research Data Management, Research Software Management, Include In Dalia
Collaborative working and Version Control with Git[Hub]#
Robert Haase
Published 2025-05-10
Licensed CC-BY-4.0
Working together on the internet presents us with new challenges: Who uploaded a file and when? Who contributed to the project when and why? How can content be merged when multiple team members make changes at the same time? The version control tool Git offers a comprehensive solution to these questions. The online platform GitHub.com provides a Git-driven platform that enables effective collaboration. Attendees of this hands-on tutorial will learn:
Introduction to version control with Git[Hub]
Working with Git: Pull requests
Resolving merge conflicts
Artificial intelligence that can respond to GitHub issues
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Combining the BIDS and ARC Directory Structures for Multimodal Research Data Organization#
Torsten Stöter, Tobias Gottschall, Andrea Schrager, Peter Zentis, Monica Valencia-Schneider, Niraj Kandpal, Werner Zuschratter, Astrid Schauss, Timo Dickscheid, Timo Mühlhaus, Dirk von Suchodoletz
Published 2023-09-12
Licensed CC-BY-4.0
Interdisciplinary collaboration and integration of large and diverse datasets are becoming increasingly important. Answering complex research questions requires combining and analysing multimodal datasets. Research data management follows the FAIR principles making data findable, accessible, interoperable, and reusable. However, there are challenges in capturing the entire research cycle and contextualizing data according, not only for the DataPLANT and NFDI4BIOIMAGE communities. To address these challenges, DataPLANT developed a data structure called Annotated Research Context (ARC). The Brain Imaging Data Structure (BIDS) originated from the neuroimaging community extended for microscopic image data. Both concepts provide standardised and file system based data storage structures for organising and sharing research data accompanied with metadata. We exemplarily compare the ARC and BIDS designs and propose structural and metadata mapping.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
Content type: Poster
Conda, Container and Bots - How to Build and Maintain Tool Dependencies in Workflows and Training Materials#
Paul Zierep, Sanjay Kumar Srikakulam, Sebastian Schaaf, Bjoern Gruening
Published 2023-09-07
Licensed CC-BY-4.0
The lifecycle of scientific tools comprises the creation of code releases, packages and containers which can be deployed into cloud platforms, such as the Galaxy Project, where they are run and integrated into workflows. The tools and workflows are further used to create training material that benefits a broad community. The need to organize and streamline this tool development lifecycle has led to a sophisticated development and deployment architecture.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
Content type: Publication
Developing a Training Strategy#
Robert Haase
Published 2024-11-08
Licensed CC-BY-4.0
When training people in topics such as programming, bio-image analysis or data science, it makes sense to define a training strategy with a wider perspective than just trainees needs. This slide deck gives insights into aspects to consider when defining a training strategy. It considers funder’s interests, financial aspects, metrics / goals, steps towards sustainability and opportunities for outreach and for founding future collaborations.
Tags: Nfdi4Bioimage, Artificial Intelligence, Include In Dalia
Development FAIR image analysis workflows and RDM pipelines in Galaxy#
Riccardo Massei, Beatriz Serrano-Solano, Anne Fouilloux, Björg Gruening, Yi Sun, Diana Chiang, Matthias Bernt, Leonid Kostrykin
Published 2025-09-10
Licensed CC-BY-4.0
Imaging is crucial across various scientific disciplines, particularly in life sciences, where it plays a key role in studies ranging from single molecules to whole organisms. However, the complexity and sheer volume of image data present significant challenges. Managing and analyzing this data efficiently requires well-defined image processing tools and analysis pipelines that align with the FAIR principles—ensuring they are findable, accessible, interoperable, and reusable across different domains. In the frame of NFDI4BIOIMAGE1 (the National Research Data Infrastructure focusing on bioimaging in Germany), we want to find viable solutions for storing, processing, analyzing, and sharing bioimaging data. In particular, we want to develop solutions to make findable and machine-readable metadata developing analysis pipelines. In scientific research, such pipelines are crucial for maintaining data integrity, supporting reproducibility, and enabling interdisciplinary collaboration. These tools can be used by different users to retrieve images based on specific attributes as well as support quality control by identifying appropriate metadata. Galaxy, an open-source, web-based platform for data-intensive research, offers a solution by enabling the construction of reproducible pipelines for image analysis2. By integrating popular analysis software like CellProfiler and connecting with cloud services such as OMERO and IDR, Galaxy facilitates the seamless access and management of image data. This capability is particularly valuable in bioimaging, where automated pipelines can streamline the handling of complex metadata, ensuring data integrity and fostering interdisciplinary collaboration. This approach not only increases the efficiency of RDM processes in bioimaging but also contributes to the broader scientific community’s efforts to embrace FAIR principles, ultimately advancing scientific discovery and innovation. In the present poster, we showed how to integrate RDM processes and tools in Galaxy. We will showcase how Images can be enriched with metadata (i.e. key-value pairs, tags, raw data, regions of interest) and uploaded to a target OME Remote Objects (OMERO) server using a novel set of OMERO tools developed with Galaxy3. Workflows give the possibility to the user to intuitively fetch images from the local server and perform image analysis (i.e. annotation). Furthermore, we will show the potential integration of eletronic lab books such as eLabFTW4, cloud storage systems (i.e. OneData)5 and interactive norebooks (Jupyter Notebooks) 6 in the Galaxy pipeline.
Tags: Nfdi4Bioimage, Exclude From Dalia
Engineering a Software Environment for Research Data Management of Microscopy Image Data in a Core Facility#
Kunis
Published 2022-05-30
This thesis deals with concepts and solutions in the field of data management in everyday scientific life for image data from microscopy. The focus of the formulated requirements has so far been on published data, which represent only a small subset of the data generated in the scientific process. More and more, everyday research data are moving into the focus of the principles for the management of research data that were formulated early on (FAIR-principles). The adequate management of this mostly multimodal data is a real challenge in terms of its heterogeneity and scope. There is a lack of standardised and established workflows and also the software solutions available so far do not adequately reflect the special requirements of this area. However, the success of any data management process depends heavily on the degree of integration into the daily work routine. Data management must, as far as possible, fit seamlessly into this process. Microscopy data in the scientific process is embedded in pre-processing, which consists of preparatory laboratory work and the analytical evaluation of the microscopy data. In terms of volume, the image data often form the largest part of data generated within this entire research process. In this paper, we focus on concepts and techniques related to the handling and description of this image data and address the necessary basics. The aim is to improve the embedding of the existing data management solution for image data (OMERO) into the everyday scientific work. For this purpose, two independent software extensions for OMERO were implemented within the framework of this thesis: OpenLink and MDEmic. OpenLink simplifies the access to the data stored in the integrated repository in order to feed them into established workflows for further evaluations and enables not only the internal but also the external exchange of data without weakening the advantages of the data repository. The focus of the second implemented software solution, MDEmic, is on the capturing of relevant metadata for microscopy. Through the extended metadata collection, a corresponding linking of the multimodal data by means of a unique description and the corresponding semantic background is aimed at. The configurability of MDEmic is designed to address the currently very dynamic development of underlying concepts and formats. The main goal of MDEmic is to minimise the workload and to automate processes. This provides the scientist with a tool to handle this complex and extensive task of metadata acquisition for microscopic data in a simple way. With the help of the software, semantic and syntactic standardisation can take place without the scientist having to deal with the technical concepts. The generated metadata descriptions are automatically integrated into the image repository and, at the same time, can be transferred by the scientists into formats that are needed when publishing the data.
Tags: Nfdi4Bioimage, Research Data Managementv, Include In Dalia
Explainable AI for Computer Vision#
Robert Haase
Published 2025-03-09
Licensed CC-BY-4.0
In this slide deck we learn about the basics of Explainable Artificial Intelligence with a soft focus on Computer Vision. We take a deeper dive in one method: Gradient Class Activation Maps. Releated exercise materials are available online: https://haesleinhuepf.github.io/xai/
Tags: Nfdi4Bioimage, Bioimage Analysis, Artificial Intelligence, Include In Dalia
I3D:bio’s OMERO training material: Re-usable, adjustable, multi-purpose slides for local user training#
Christian Schmidt, Michele Bortolomeazzi, Tom Boissonnet, Carsten Fortmann-Grote, Julia Dohle, Peter Zentis, Niraj Kandpal, Susanne Kunis, Thomas Zobel, Stefanie Weidtkamp-Peters, Elisa Ferrando-May
Published 2023-11-13
Licensed CC-BY-4.0
The open-source software OME Remote Objects (OMERO) is a data management software that allows storing, organizing, and annotating bioimaging/microscopy data. OMERO has become one of the best-known systems for bioimage data management in the bioimaging community. The Information Infrastructure for BioImage Data (I3D:bio) project facilitates the uptake of OMERO into research data management (RDM) practices at universities and research institutions in Germany. Since the adoption of OMERO into researchers’ daily routines requires intensive training, a broad portfolio of training resources for OMERO is an asset. On top of using the OMERO guides curated by the Open Microscopy Environment Consortium (OME) team, imaging core facility staff at institutions where OMERO is used often prepare additional material tailored to be applicable for their own OMERO instances. Based on experience gathered in the Research Data Management for Microscopy group (RDM4mic) in Germany, and in the use cases in the I3D:bio project, we created a set of reusable, adjustable, openly available slide decks to serve as the basis for tailored training lectures, video tutorials, and self-guided instruction manuals directed at beginners in using OMERO. The material is published as an open educational resource complementing the existing resources for OMERO contributed by the community.
Tags: OMERO, Research Data Management, Nfdi4Bioimage, I3Dbio, Include In Dalia
Content type: Slides, Video
https://zenodo.org/records/8323588
https://www.youtube.com/playlist?list=PL2k-L-zWPoR7SHjG1HhDIwLZj0MB_stlU
Increasing the FAIRness of electron microscopy data in life and material science research#
Cornelia Wetzker
Published 2025-08-31
Licensed CC-BY-4.0
The poster introduces the consortium NFDI4BIOIMAGE and presents tools of research data management in microscopy to increase the FAIRness of data at the Microscopy Conference in Karlsruhe 2025. On site, it is presented in booth 57 for joint introduction of the national research data infrastructure (NFDI) consortia matWERK, FAIRmat and NFDI4BIOIMAGE. C.W. is funded by the German consortium NFDI4BIOIMAGE (Deutsche Forschungsgemeinschaft, grant number NFDI 46/1, project number 501864659).
Tags: Nfdi4Bioimage, Include In Dalia
Introducing OMERO-vitessce: an OMERO.web plugin for multi-modal data#
Michele Bortolomeazzi, Christian Schmidt, Jan-Philipp Mallm
Published 2025-02-07
Licensed CC-BY-4.0
omero-vitessce: an OMERO.web plugin for multi-modal data viewing. OMERO is the most used research data management system (RDM) in the bioimaging domain, and has been adopted as a centralized RDM solution by several academic and research institutions. A main reason for this is the ability to directly view and annotate images from a web-based interface. However, this feature of OMERO is currently underpowered for the visualization of very large or multimodal datasets. These datasets, are becoming a more and more common foundation for biological and biomedical studies, due to the recent developments in imaging, and sequencing technologies which enabled their application to spatial-omics. In order to begin to provide this multimodal-data capability to OMERO, we developed omero-vitessce (NFDI4BIOIMAGE/omero-vitessce), a new OMERO.web plugin for viewing data stored in OMERO with the Vitessce (http://vitessce.io/) multimodal data viewer. omero-vitessce can be installed as an OMERO.web plugin with PiPy (https://pypi.org/project/omero-vitessce/), and allows users to set up interactive visualizations of their images of cells and tissues through interactive plots which are directly linked to the image. This enables the visual exploration of bioimage-analysis results and of multimodal data such as those generated through spatial-omics experiments. The data visualization is highly customizable and can be configured not only through custom configuration files, but also with the graphical interface provided by the plugin, thus making omero-vitessce a highly user-friendly solution for multimodal data viewing. most biological datasets. We plan to extend the interoperability of omero-vitessce with the OME-NGFF and SpatialData file formats to leverage the efficiency of these cloud optimized formats. The three files in this Zenodo Record are all the same poster saved in different format all with high resolution images.
Tags: Nfdi4Bioimage, Exclude From Dalia
Introduction to OMERO - Frankfurt - online#
Michele Bortolomeazzi, Tom Boissonnet
Published 2025-04-05
Licensed CC-BY-4.0
These slides were presented during an online introductory session to OMERO for the UB Frankfurt. The two-hour session consisted of a first part highlighting the benefits that image data management brings to the lab. The second part showcased image analysis workflows with a Fiji macro and a Python notebook.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
JIPipe Spring Course (JSC) 2025: Workshop Recordings, Slides, Homework, and Materials#
Ruman Gerst, Zoltán Cseresnyés, Marc Thilo Figge
Published 2025-05-12:T13:37:00+00:00
Licensed CC-BY-4.0
The course gives a basic introduction into microscopy, optics, and image analysis. This is followed by interactive tutorials that explain the basics of creating fully automated image analysis workflows in JIPipe using a simple blobs analysis and intermediate-level quantification of LSFM kidney images. JIPipe-specific features including annotation-guided batch processing, organization with graph compartments, expressions and path processing, and project-wide metadata and parameters are also established. Finally, an advanced real-world pipeline is showcased with detailed guidance through the individual components that include integrations of Cellpose and TrackMate.
Tags: Nfdi4Bioimage, Jipipe, Bioimage Analysis, Include In Dalia
Content type: Workshop, Video, Tutorial, Slides
Key-Value pair template for annotation in OMERO for light microscopy data acquired with AxioScan7 - Core Facility Cellular Imaging (CFCI)#
Silke Tulok, Anja Nobst, Anett Jannasch, Tom Boissonnet, Gunar Fabig
Published 2024-06-28
Licensed CC-BY-4.0
This Key-Value pair template is used for the data documentation during imaging experiments and the later data annotation in OMERO. It is tailored for the usage and image acquisition at the slide scanning system Zeiss AxioScan 7 in the Core Facility Cellular Imaging (CFCI). It contains important metadata of the imaging experiment, which are not saved in the corresponding imaging files. All users of the Core Facility Cellular Imaging are trained to use that file to document their imaging parameters directly during the data acquisition with the possibility for a later upload to OMERO. Furthermore, there is a corresponding public example image used in the publication “Setting up an institutional OMERO environment for bioimage data: perspectives from both facility staff and users” and is available here: https://omero.med.tu-dresden.de/webclient/?show=image-33248 This template was developed by the CFCI staff during the setup and usage of the AxioScan 7 and is based on the REMBI recommendations (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606015). With this template it is possible to create a csv-file, that can be used to annotate an image or dataset in OMERO using the annotation script (ome/omero-scripts). How to use:
fill the template sheet with your metadata select and copy the data range containing the Keys and Values open a new excel sheet and paste transpose in cell A1 Important: cell A1 contains always the name ‘dataset’ and cell A2 contains the exact name of the image/dataset, which should be annotated in OMERO save the new excel sheet in csv-file (comma separated values) format
An example can be seen in sheet 3 ‘csv_AxioScan’. Important note: The code has to be 8-Bit UCS transformation format (UTF-8) otherwise several characters (for example µ, %,°) might be not able to decode by the annotation script. We encountered this issue with old Microsoft-Office versions (MS Office 2016). Note: By filling the values in the excel sheet, avoid the usage of comma as decimal delimiter. See cross reference: 10.5281/zenodo.12547566 Key-Value pair template for annotation of datasets in OMERO for light- and electron microscopy data within the research group of Prof. Mueller-Reichert 10.5281/zenodo.12546808 Key-Value pair template for annotation of datasets in OMERO (PERIKLES study)
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Key-Value pair template for annotation of datasets in OMERO (PERIKLES study)#
Anett Jannasch, Silke Tulok, Vanessa Aphaia Fiona Fuchs, Tom Boissonnet, Christian Schmidt, Michele Bortolomeazzi, Gunar Fabig, Chukwuebuka Okafornta
Published 2024-06-26
Licensed CC-BY-4.0
This is a Key-Value pair template used for the annotation of datasets in OMERO. It is tailored for a research study (PERIKLES project) on the biocompatibility of newly designed biomaterials out of pericardial tissue for cardiovascular substitutes (https://doi.org/10.1063/5.0182672) conducted in the research department of Cardiac Surgery at the Faculty of Medicine Carl Gustav Carus at the Technische Universität Dresden . A corresponding public example dataset is used in the publication “Setting up an institutional OMERO environment for bioimage data: perspectives from both facility staff and users” and is available here (https://omero.med.tu-dresden.de/webclient/?show=dataset-1557). The template is based on the REMBI recommendations (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606015) and it was developed during the PoL-Bio-Image Analysis Symposium in Dresden Aug 28th- Sept 1th 2023. With this template it is possible to create a csv-file, that can be used to annotate a dataset in OMERO using the annotation script (ome/omero-scripts). How to use: select and copy the data range containing Keys and Values open a new excel sheet and paste transpose in column B1 type in A1 ‘dataset’ insert in A2 the exact name of the dataset, which should be annotated in OMERO save the new excel sheet in csv- (comma seperated values) file format
Example can be seen in sheet 1 ‘csv import’. Important note; the code has to be 8-Bit UCS transformation format (UTF-8) otherwise several characters (for example µ, %,°) might not be able to decode by the annotation script. We encountered this issue with old Microsoft Office versions (e.g. MS Office 2016). Note: By filling the values in the excel sheet, avoid the usage of decimal delimiter. See cross reference: 10.5281/zenodo.12547566 Key-Value pair template for annotation of datasets in OMERO (light- and electron microscopy data within the research group of Prof. Mueller-Reichert) 10.5281/zenodo.12578084 Key-Value pair template for annotation in OMERO for light microscopy data acquired with AxioScan7 - Core Facility Cellular Imaging (CFCI)
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Linking of Research (Meta-)data in OMERO to Foster FAIR Data in Plasma Science#
Robert Wagner, Mohsen Ahmadi, Dagmar Waltemath, Kristina Yordanova, Becker, Markus M.
Published 2025-09-10
Licensed CC-BY-4.0
Applied plasma research involves several disciplines such as physics, medicine and biology to solve application-oriented problems, often generating large and heterogeneous experimental data sets. The descriptions and metadata describing these interdisciplinary scientific investiga-tions is stored in distributed systems (e.g., physical laboratory notebooks or electronic labora-tory notebooks (ELN) like eLabFTW [1]), and the experimental data are either stored locally within the laboratories or on centralized institutional storage systems. As a result, the collected information often has to be tediously assembled for processing into publications. The workflow represented in Figure 1 addresses this suboptimal situation and promotes the combination of the image database OMERO [2], the ELN system eLabFTW, the research data management tool Adamant [3] and Python scripts for handling microscopy images in plasma life science and plasma medicine [4]. This workflow highlights how the developments from the NFDI4BIOIMAGE consortium can be brought into practical applications by addressing the specific demands of plasma science, where domain-specific metadata is essential for effective data interpretation and reuse. It showcases the benefits of FAIR [5] metadata combining do-main-specific requirements with method-specific solutions. Similar to most imaging workflows, image analysis in plasma research requires metadata from several sections of the experiment. Moreover, the plasma-related metadata are essential for the experimental context and must be included in the analysis, e.g. to describe the influence of plasma on the treated sample. Therefore, the metadata schema Plasma-MDS [6] is adapted to collect plasma-related metadata, such as information on the plasma species having a major impact on the treated samples. Alongside Plasma-MDS, the Recommended Metadata for Bio-logical Images (REMBI) standard [7] is used for the biological metadata such as the sample preparation and treatment procedures. The collection of these metadata is realized using Adamant, which enables the beginner-friendly collection of structured metadata. The tool presents JSON schemas in easy-to-read and easy-to-fill HTML forms, enabling metadata validation. Once completed and validated, the metadata are uploaded directly to eLabFTW using Adamant’s workflow functionalities. The images from the treated samples are uploaded to OMERO by OMERO.insight and afterwards automatically annotated via Python scripts. These scripts take previously collected metadata from the related eLabFTW experiments and the microscope description metadata collected by the Micro Meta App [8], which are also stored in eLabFTW. The metadata is categorized and annotated according to the various data organizational levels within OMERO, specifically fo-cusing on project and dataset hierarchies, as well as screens that are composed of plates, which in turn contain wells. Screens resemble microwell plates, commonly used in a variety of biological experiments. The hieraic organization of metadata significantly enhances the ease of reusing images and associated metadata for subsequent processing and analysis. By efficiently distributing and reducing large metadata sets to an acceptable level, while simultaneously eliminating redun-dancies, this approach facilitates straightforward analyses with tools like ImageJ [9] and FIJI [10], thanks to the close association of metadata with the images themselves. In summary, one of the application-specific developments within the NFDI4BIOIMAGE consor-tium is presented, which contributes to the adoption of the FAIR principles in laboratory envi-ronments. Further work will address the integration of ontologies for the semantic description of data and metadata.
Tags: Nfdi4Bioimage, Bioimage Analysis, Exclude From Dalia
Metadata in Bioimaging#
Josh Moore, Susanne Kunis
Published 2025-03-25
Licensed CC-BY-4.0
Presentation given to the Search & Harvesting workgroup of the Metadata section of NFDI on March 25th, 2025
Tags: Nfdi4Bioimage, Exclude From Dalia
NFDI - Daten als gemeinsames Gut für exzellente Forschung, organisiert durch die Wissenschaft in Deutschland.#
Licensed UNKNOWN
Schritt für Schritt verbessern wir die Nutzungsmöglichkeiten von Daten für Wissenschaft und Gesellschaft. Durch unser Zusammenwirken im NFDI-Verein entsteht eine Dachorganisation für das Forschungsdatenmanagement in allen Wissenschaftszweigen.
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Content type: Website
NFDI4BIOIMAGE#
Carsten Fortmann-Grote
Licensed CC-BY-4.0
Presentation was given at the 2nd MPG-NFDI Workshop on April 18th about e NFDI4BIOIMAGE Consortium, FAIRification of Image (meta)data, Zarr, RFC, Training (TA5), contributing.
Tags: Research Data Management, Bioimage Analysis, FAIR-Principles, Zarr, Nfdi4Bioimage, Include In Dalia
Content type: Slides
NFDI4BIOIMAGE - An Initiative for a National Research Data Infrastructure for Microscopy Data#
Christian Schmidt, Elisa Ferrando-May
Published 2021-04-29
Licensed CCY-BY-SA-4.0
Align existing and establish novel services & solutions for data management tasks throughout the bioimage data lifecycle.
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Content type: Conference Abstract, Slides
NFDI4BIOIMAGE - National Research Data Infrastructure for Microscopy and BioImage Analysis - Online Kick-Off 2023#
Stefanie Weidtkamp-Peters
Licensed CC-BY-4.0
NFDI4BIOIMAGE core mission, bioimage data challenge, task areas, FAIR bioimage workflows.
Tags: Research Data Management, FAIR-Principles, Bioimage Analysis, Nfdi4Bioimage, Include In Dalia
Content type: Slides
NFDI4BIOIMAGE - National Research Data Infrastructure for Microscopy and BioImage Analysis [conference talk: The Pelagic Imaging Consortium meets Helmholtz Imaging, 5.10.2023, Hamburg]#
Riccardo Massei
Licensed CC-BY-4.0
NFDI4BIOIMAGE is a consortium within the framework of the National Research Data Infrastructure (NFDI) in Germany. In this talk, the consortium and the contribution to the work programme by the Helmholtz Centre for Environmental Research (UFZ) in Leipzig are outlined.
Tags: Research Data Management, Bioimage Analysis, Nfdi4Bioimage, Exclude From Dalia
Content type: Slides
NFDI4BIOIMAGE - a consortium of the National Research Data Infrastructure#
Nfdi4Bioimage
Licensed UNKNOWN
Tags: Bioimage Analysis, Research Data Management, Nfdi4Bioimage, Exclude From Dalia
Content type: Collection
NFDI4BIOIMAGE data management illustrations by Henning Falk#
NFDI4BIOIMAGE Consortium
Published 2024-11-29
Licensed CC-BY-4.0
These illustrations were contracted by the Heinrich Heine University Düsseldorf in the frame of the consortium NFDI4BIOIMAGE from Henning Falk for the purpose of education and public outreach. The illustrations are free to use under a CC-BY 4.0 license.AttributionPlease include an attribution similar to: “Data annoation matters”, NFDI4BIOIMAGE Consortium (2024): NFDI4BIOIMAGE data management illustrations by Henning Falk, Zenodo, https://doi.org/10.5281/zenodo.14186100, is used under a CC-BY 4.0 license. Modifications to this illustration include cropping.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
NFDI4BIOIMAGE: Perspective for a national bioimaging standard#
Josh Moore, Susanne Kunis
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Exclude From Dalia
Content type: Publication
NFDI4Bioimage - TA3-Hackathon - UoC-2023 (Cologne Hackathon)#
Mohamed M. Abdrabbou, Mehrnaz Babaki, Tom Boissonnet, Michele Bortolomeazzi, Eik Dahms, Vanessa A. F. Fuchs, Moritz Hoevels, Niraj Kandpal, Christoph Möhl, Joshua A. Moore, Astrid Schauss, Andrea Schrader, Torsten Stöter, Julia Thönnißen, Monica Valencia-S., H. Lukas Weil, Jens Wendt and Peter Zentis
Licensed CC-BY-4.0
Tags: Arc, Dataplant, Hackathon, Nfdi4Bioimage, OMERO, Python, Research Data Management, Exclude From Dalia
Content type: Event, Publication, Documentation
NFDI4Bioimage - TA3-Hackathon - UoC-2023 (Cologne-Hackathon-2023, GitHub repository)#
Mohamed Abdrabbou, Mehrnaz Babaki, Tom Boissonnet, Michele Bortolomeazzi, Eik Dahms, Vanessa Fuchs, A. F. Moritz Hoevels, Niraj Kandpal, Christoph Möhl, Joshua A. Moore, Astrid Schauss, Andrea Schrader, Torsten Stöter, Julia Thönnißen, Monica Valencia-S., H. Lukas Weil, Jens Wendt, Peter Zentis
Licensed CC-BY-4.0
This repository documents the first NFDI4Bioimage - TA3-Hackathon - UoC-2023 (Cologne Hackathon), where topics like ‘Interoperability’, ‘REMBI / Mapping’, and ‘Neuroglancer (OMERO / zarr)’ were explored through collaborative discussions and workflow sessions, culminating in reports that bridge NFDI4Bioimage to DataPLANT. Funded by various DFG initiatives, this event emphasized documentation and use cases, contributing preparatory work for future interoperability projects at the 2nd de.NBI BioHackathon in Bielefeld.
Tags: Research Data Management, FAIR-Principles, Bioimage Analysis, Nfdi4Bioimage, Exclude From Dalia
Content type: Github Repository
NFDI4Bioimage Calendar 2024 October; original image#
Christian Jüngst, Peter Zentis
Published 2024-09-25
Licensed CC-BY-4.0
Raw microscopy image from the NFDI4Bioimage calendar October 2024
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies#
Josh Moore, Chris Allan, Sébastien Besson, Jean-Marie Burel, Erin Diel, David Gault, Kevin Kozlowski, Dominik Lindner, Melissa Linkert, Trevor Manz, Will Moore, Constantin Pape, Christian Tischer, Jason R. Swedlow
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Content type: Publication
OME2024 NGFF Challenge Results#
Josh Moore
Published 2024-11-01
Licensed CC-BY-4.0
Presented at the 2024 FoundingGIDE event in Okazaki, Japan: https://founding-gide.eurobioimaging.eu/event/foundinggide-community-event-2024/ Note: much of the presentation was a demonstration of the OME2024-NGFF-Challenge – https://ome.github.io/ome2024-ngff-challenge/ especially of querying an extraction of the metadata (ome/ome2024-ngff-challenge-metadata)
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
OMERO for microscopy research data management#
Thomas Zobel, Sarah Weischner, Jens Wendt
Licensed ALL RIGHTS RESERVED
A use case example from the Münster Imaging Network
Tags: Nfdi4Bioimage, OMERO, Research Data Management, Exclude From Dalia
Content type: Publication
https://analyticalscience.wiley.com/do/10.1002/was.0004000267/
OMExcavator: a tool for exporting and connecting domain-specific metadata in a wider knowledge graph#
Stefan Dvoretskii, Michele Bortolomeazzi, Marco Nolden, Christian Schmidt, Klaus Maier-Hein, Josh Moore
Published 2025-02-21
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Exclude From Dalia
Overview of the Galaxy OMERO-suite - Upload images and metadata in OMERO using Galaxy#
Riccardo Massei, Björn Grüning
Published 2024-12-02
Licensed CC-BY-4.0
Tags: OMERO, Galaxy, Metadata, Nfdi4Bioimage, Include In Dalia
Content type: Tutorial, Framework, Workflow
Reproducible Bio-Image Analysis using Python, Napari, Jupyter and AI#
Robert Haase
Published 2025-09-09
Licensed CC-BY-4.0
In this slide deck we learn how to write reproducible bio-image analysis code in Jupyter notebooks. Goal is not just to have code running elsewhere reproducibly, but also enabling others to understand workflows to enable them reproducing the analysis also in their mind and potentially other tools. Additionally we cover how to generate Jupyter notebooks from Napari and using artificial intelligence, namely bia-bob.
Tags: Nfdi4Bioimage, Bioimage Analysis, Include In Dalia
Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey#
Christian Schmidt, Janina Hanne, Josh Moore, Christian Meesters, Elisa Ferrando-May, Stefanie Weidtkamp-Peters, members of the NFDI4BIOIMAGE initiative
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Content type: Publication
Setting up a data management infrastructure for bioimaging#
Susanne Kunis, Karen Bernhardt, Michael Hensel
Licensed UNKNOWN
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
Content type: Publication
Setting up an institutional OMERO environment for bioimage data: Perspectives from both facility staff and users#
Anett Jannasch, Silke Tulok, Chukwuebuka William Okafornta, Thomas Kugel, Michele Bortolomeazzi, Tom Boissonnet, Christian Schmidt, Andy Vogelsang
Published 2024-09-14
Licensed CC-BY-4.0
Modern bioimaging core facilities at research institutions are essential for managing and maintaining high-end instruments, providing training and support for researchers in experimental design, image acquisition and data analysis.
Tags: Nfdi4Bioimage, OMERO, Bioimage Analysis, Exclude From Dalia
Content type: Publication
Structuring of Data and Metadata in Bioimaging: Concepts and technical Solutions in the Context of Linked Data#
Sarah Weischer, Jens Wendt, Thomas Zobel
Published 2022-07-12
Licensed CC-BY-4.0
Provides an overview of contexts, frameworks, and models from the world of bioimage data as well as metadata. Visualizes the techniques for structuring this data as Linked Data. (Walkthrough Video: https://doi.org/10.5281/zenodo.7018928 )
Content:
Types of metadata
Data formats
Data Models Microscopy Data
Tools to edit/gather metadata
ISA Framework
FDO Framework
Ontology
RDF
JSON-LD
SPARQL
Knowledge Graph
Linked Data
Smart Data
...
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
The Information Infrastructure for BioImage Data (I3D:bio) project to advance FAIR microscopy data management for the community#
Christian Schmidt, Michele Bortolomeazzi, Tom Boissonnet, Julia Dohle, Tobias Wernet, Janina Hanne, Roland Nitschke, Susanne Kunis, Karen Bernhardt, Stefanie Weidtkamp-Peters, Elisa Ferrando-May
Published 2024-03-04
Licensed CC-BY-4.0
Research data management (RDM) in microscopy and image analysis is a challenging task. Large files in proprietary formats, complex N-dimensional array structures, and various metadata models and formats can make image data handling inconvenient and difficult. For data organization, annotation, and sharing, researchers need solutions that fit everyday practice and comply with the FAIR (Findable, Accessible, Interoperable, Reusable) principles. International community-based efforts have begun creating open data models (OME), an open file format and translation library (OME-TIFF, Bio-Formats), data management software platforms, and microscopy metadata recommendations and annotation tools. Bringing these developments into practice requires support and training. Iterative feedback and tool improvement is needed to foster practical adoption by the scientific community. The Information Infrastructure for BioImage Data (I3D:bio) project works on guidelines, training resources, and practical assistance for FAIR microscopy RDM adoption with a focus on the management platform OMERO and metadata annotations.
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
The role of Helmholtz Centers in NFDI4BIOIMAGE - A national consortium enhancing FAIR data management for microscopy and bioimage analysis#
Riccardo Massei, Christian Schmidt, Michele Bortolomeazzi, Julia Thoennissen, Jan Bumberger, Timo Dickscheid, Jan-Philipp Mallm, Elisa Ferrando-May
Published 2024-06-06
Licensed CC-BY-4.0
Germany’s National Research Data Infrastructure (NFDI) aims to establish a sustained, cross-disciplinary research data management (RDM) infrastructure that enables researchers to handle FAIR (findable, accessible, interoperable, reusable) data. While FAIR principles have been adopted by funders, policymakers, and publishers, their practical implementation remains an ongoing effort. In the field of bio-imaging, harmonization of data formats, metadata ontologies, and open data repositories is necessary to achieve FAIR data. The NFDI4BIOIMAGE was established to address these issues and develop tools and best practices to facilitate FAIR microscopy and image analysis data in alignment with international community activities. The consortium operates through its Data Stewards team to provide expertise and direct support to help overcome RDM challenges. The three Helmholtz Centers in NFDI4BIOIMAGE aim to collaborate closely with other centers and initiatives, such as HMC, Helmholtz AI, and HIP. Here we present NFDI4BIOIMAGE’s work and its significance for research in Helmholtz and beyond
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Thinking data management on different scales#
Susanne Kunis
Licensed CC-BY-4.0
Presentation given at PoL BioImage Analysis Symposium Dresden 2023
Tags: Research Data Management, Nfdi4Bioimage, Include In Dalia
Content type: Slides
Towards Preservation of Life Science Data with NFDI4BIOIMAGE#
Robert Haase
Published 2024-09-03
Licensed CC-BY-4.0
This talk will present the initiatives of the NFDI4BioImage consortium aimed at the long-term preservation of life science data. We will discuss our efforts to establish metadata standards, which are crucial for ensuring data reusability and integrity. The development of sustainable infrastructure is another key focus, enabling seamless data integration and analysis in the cloud. We will take a look at how we manage training materials and communicate with our community. Through these actions, NFDI4BioImage seeks to enable FAIR bioimage data management for German researchers, across disciplines and embedded in the international framework.
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Towards open and standardised imaging data: an introduction to Bio-Formats, OME-TIFF, and OME-Zarr#
Josh Moore
Published 2025-05-28
Licensed CC-BY-4.0
https://www.ebi.ac.uk/training/events/towards-open-and-standardised-imaging-data-introduction-bio-formats-ome-tiff-and-ome-zarr/ Microscopy and bioimaging technologies are fundamental tools for exploring biological systems, generating large, multidimensional datasets rich in experimental detail. However, the bioimaging community has historically faced major challenges around data handling: vendor-specific proprietary formats, fragmented metadata storage, and increasingly large dataset sizes that outstrip traditional storage and computing solutions. In this webinar, key open technologies developed by the Open Microscopy Environment (OME) to address these challenges were presented. Specifically, the Bio-Formats library for accessing diverse proprietary file formats, the OME-TIFF standard for archival data storage, and the OME-Zarr format for cloud-native, scalable bioimaging workflows were presented.
Tags: Nfdi4Bioimage, Include In Dalia
Training Computational Skills in the Age of AI#
Robert Haase
Published 2024-11-06
Licensed CC-BY-4.0
Artificial intelligence (AI) and large language models (LLMs) are changing the way we use computers in science. This slide deck introduces ways for using AI and LLMs for making training materials and for exchanging knowledge about how to use AI in joint discussions between humans and LLM-based AI-systems.
Tags: Nfdi4Bioimage, Artificial Intelligence, Include In Dalia
Vision Language Models for Bio-image Data Science#
Robert Haase
Published 2025-06-25
Licensed CC-BY-4.0
In this talk, I demonstrate potential use-cases for vision-language models (VLM) in bio-image data science, focusing on how to analyse microscopy image data. It covers these use-cases:
cell counting bounding-box segmentation image descriptions VLMs guessing which algorithm to use for processing Data analysis code generation Answering github issues
The talk also points at a number of VLM-based open-source tools which start reshaping the scientific bio-image data science domain:
bia-bob unprompted git-bob napari-chatgpt bioimage.io chatbot
Tags: Nfdi4Bioimage, Bioimage Analysis, Artificial Intelligence, Include In Dalia
Welcome to BioImage Town#
Josh Moore
Licensed CC-BY-4.0
Welcome at NFDI4BIOIMAGE All-Hands Meeting in Düsseldorf, Germany, October 16, 2023
Tags: OMERO, Bioimage Analysis, Nfdi4Bioimage, Exclude From Dalia
Content type: Slides
Who you gonna call? - Data Stewards to the rescue#
Vanessa Aphaia Fiona Fuchs, Jens Wendt, Maximilian Müller, Mohsen Ahmadi, Riccardo Massei, Cornelia Wetzker
Licensed CC-BY-4.0
The Data Steward Team of the NFDI4BIOIMAGE consortium presents themselves and the services (including the Helpdesk) that we offer.
Tags: Research Data Management, Bioimage Analysis, Data Stewardship, Nfdi4Bioimage, Include In Dalia
Content type: Poster
Workflow for user introduction into microscopy, OMERO and data management at Center for Advanced imaging#
Ksenia Krooß, Fuchs, Vanessa Aphaia Fiona, Tom Boissonnet, Stefanie Weidtkamp-Peters
Published 2025-03-07
Licensed CC-BY-4.0
At the Center for Advanced Imaging (CAi) at the Heinrich Heine University Düsseldorf, Germany, we have established a workflow to guide users through all aspects of bioimaging. The process begins with an initial consultation with our imaging specialists regarding microscopy techniques for their specific project. Users then receive training in microscope operation, ensuring they can handle the equipment effectively. If needed, our specialists also provide support in image analysis. Next, we introduce users to OMERO, highlighting its features and the advantages of using a bioimage data management system. They are then trained to structure and annotate their data within OMERO according to the Recommended Metadata for Biological Images (REMBI), taking their specific research topics into account. As users prepare for data publication, we assist with data organization and repository uploads. Our goal is to educate researchers in managing bioimage data throughout its entire lifecycle, with a strong emphasis on the FAIR (findable, accessible, interoperable, reusable) principles.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
Zarr - A Cloud-Optimized Storage for Interactive Access of Large Arrays#
Josh Moore, Susanne Kunis
Published 2023-09-07
Licensed CC-BY-4.0
For decades, the sharing of large N-dimensional datasets has posed issues across multiple domains. Interactively accessing terabyte-scale data has previously required significant server resources to properly prepare cropped or down-sampled representations on the fly. Now, a cloud-native chunked format easing this burden has been adopted in the bioimaging domain for standardization. The format — Zarr — is potentially of interest for other consortia and sections of NFDI.
Tags: Nfdi4Bioimage, Bioimage Analysis, Exclude From Dalia
Content type: Publication
[CIDAS] Scalable strategies for a next-generation of FAIR bioimaging#
Josh Moore
Published 2025-01-23
Licensed CC-BY-4.0
Talk given at Georg-August-Universität Göttingen Campus Institute Data Science23rd January 2025 https://www.uni-goettingen.de/en/653203.html
Tags: Nfdi4Bioimage, Include In Dalia
[CMCB] Scalable strategies for a next-generation of FAIR bioimaging#
Josh Moore
Published 2025-01-16
Licensed CC-BY-4.0
CMCB LIFE SCIENCES SEMINARSTechnische Universität Dresden16th January 2025 https://tu-dresden.de/cmcb/crtd/news-termine/termine/cmcb-life-sciences-seminar-josh-moore-german-bioimaging-e-v-society-for-microscopy-and-image-analysis-constance
Tags: Nfdi4Bioimage, Include In Dalia
[Community Meeting 2024] Overview Team Image Data Analysis and Management#
Susanne Kunis, Thomas Zobel
Published 2024-03-08
Licensed CC-BY-4.0
Overview of Activities of the Team Image Data Analysis and Management of German BioImaging e.V.
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
[ELMI 2024] AI’s Dirty Little Secret: Without#
FAIR Data, It’s Just Fancy Math
Josh Moore, Susanne Kunis
Published 2024-05-21
Licensed CC-BY-4.0
Poster presented at the European Light Microscopy Initiative meeting in Liverpool (https://www.elmi2024.org/)
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
[ELMI 2024] AI’s Dirty Little Secret: Without FAIR Data, It’s Just Fancy Math#
Josh Moore, Susanne Kunis
Licensed CC-BY-4.0
Poster presented at the European Light Microscopy Initiative meeting in Liverpool (https://www.elmi2024.org/)
Tags: Research Data Management, FAIR-Principles, Bioimage Analysis, Nfdi4Bioimage, Include In Dalia
Content type: Poster
[ELMI2025] Bridging communities with OME-Zarr#
Christian Schmidt, Aastha Mathur, Josh Moore
Published 2025-06-04
Licensed CC-BY-4.0
Presented at ELMI2025 https://www.embl.org/about/info/course-and-conference-office/events/elmi2025/
Tags: Nfdi4Bioimage, Include In Dalia
[ELMI2025] The Road to OME-Zarr 1.0#
Josh Moore
Published 2025-06-05
Licensed CC-BY-4.0
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.
Tags: Nfdi4Bioimage, Include In Dalia
[N4BI AHM] Welcome to BioImage Town#
Josh Moore
Published 2023-10-16
Licensed CC-BY-4.0
Keynote at the NFDI4BIOIMAGE All-Hands Meeting in Düsseldorf, Germany, October 16, 2023.
Tags: Nfdi4Bioimage, Exclude From Dalia
[NFDI Tech Talk] Cloud Based Image Science#
Josh Moore, Yi Sun
Published 2025-06-02
Licensed CC-BY-4.0
Slides for the NFDI Tech Talk live streamed to https://www.youtube.com/live/bzfmE29S270 See http://nfdi.de/talks for more information.
Tags: Nfdi4Bioimage, Include In Dalia
[SWAT4HCLS 2023] NFDI4BIOIMAGE: Perspective for a national bioimage standard#
Josh Moore, Susanne Kunis
Licensed CC-BY-4.0
Poster presented at Semantic Web Applications and Tools for Health Care and Life Sciences (SWAT4HCLS 2023), Feb 13–16, 2023, Basel, Switzerland. NFDI4BIOIMAGE is a newly established German consortium dedicated to the FAIR representation of biological imaging data. A key deliverable is the definition of a semantically-compatible FAIR image object integrating RDF metadata with web-compatible storage of large n-dimensional binary data in OME-Zarr. We invite feedback from and collaboration with other endeavors during the soon-to-begin 5 year funding period.
Tags: Research Data Management, FAIR-Principles, Nfdi4Bioimage, Include In Dalia
Content type: Poster
[Short Talk] NFDI4BIOIMAGE - A consortium in the National Research Data Infrastructure#
Christian Schmidt
Licensed CC-BY-4.0
Short Talk about the NFDI4BIOIMAGE consortium presented at the RDM in (Bio-)Medicine Information Event on April 10th, 2024, organized C³RDM & ZB MED.
Tags: Research Data Management, Bioimage Analysis, Nfdi4Bioimage, Include In Dalia
Content type: Slides
[Webinar] A journey to FAIR bioimage data#
Stefanie Weidtkamp-Peters, Tom Boissonnet, Christian Schmidt
Published 2025-07-03
Licensed CC-BY-4.0
Presentation slides from an EMBL-EBI Webinar Talk within the webinar series: “How to organise and share my imaging data? - Multimodal data management for marine biologists, environmental scientists and imaging specialists” Abstract / Description Bioimaging is a pervasive and indispensable methodological approach in the life and biomedical sciences. Due to the development of new technologies and the easier access to compute resources, bioimaging experiments have become a big data discipline, facing the same challenges as other omics technologies within the life sciences. However, to fully exploit the potential of bioimage data, it is necessary to make the data FAIR. In this webinar we will present viable solutions for storing, processing, analysing, and, first and foremost, sharing bioimaging data. We will introduce services provided to the scientific community, that are dealing with various aspects of the bioimage data life cycle such as:
Where to get support for bioimage data management- Local bioimage data management: OMERO and beyond- Annotation of bioimage data: metadata, ontologies, REMBI etc- Linking your image data with experimental protocols and analysis results- Large data living in the cloud: ome.zarr- Publication of bioimage data Who is this course for? This webinar is suitable for marine biologists and environmental scientists collecting samples from the natural environment, generating, visualising, annotating and analysing large, multimodal datasets such as imaging data, and sharing their data by submitting them to public data repositories. The webinar will support you to set up an efficient data flow that is aligned with FAIR principles. This event is part of a webinar series organised by the STANDFLOW project, an initiative supported by EMBL’s Planetary biology Transversal Theme. STANDFLOW is about a collaborative effort towards creating a standardised data management workflow. The project primarily utilises imaging data derived from samples collected through the TREC (Traversing European Coastlines) and the Roscoff Culture Collection. For details on all topics covered in this series and registration information, please visit the following link: How to organise and share my imaging data?: Multimodal data management for marine biologists, and environmental scientists and imaging specialists Outcomes By the end of the webinar you will be able to:
Find resources and support for bioimage data management Get started with bioimage data annotation Identify the dos and don’ts for bioimage data publication
(taken from: https://www.ebi.ac.uk/training/events/journey-fair-bioimage-data/)
Tags: Nfdi4Bioimage, Fair Principles, Research Data Management, Include In Dalia
[Workshop Material] Fit for OMERO - How imaging facilities and IT departments work together to enable RDM for bioimaging, October 16-17, 2024, Heidelberg#
Tom Boissonnet, Bettina Hagen, Susanne Kunis, Christian Schmidt, Stefanie Weidtkamp-Peters
Published 2024-11-18
Licensed CC-BY-4.0
Fit for OMERO: How imaging facilities and IT departments work together to enable RDM for bioimaging Description: Research data management (RDM) in bioimaging is challenging because of large file sizes, heterogeneous file formats and the variability of imaging methods. The image data management system OMERO (OME Remote Objects) allows for centralized and secure storage, organization, annotation, and interrogation of microscopy data by researchers. It is an internationally well-supported open-source software tool that has become one of the best-known image data management tools among bioimaging scientists. Nevertheless, the de novo setup of OMERO at an institute is a multi-stakeholder process that demands time, funds, organization and iterative implementation. In this workshop, participants learn how to begin setting up OMERO-based image data management at their institution. The topics include:
Stakeholder identification at the university / research institute Process management, time line expectations, and resources planning Learning about each other‘s perspectives on chances and challenges for RDM Funding opportunities and strategies for IT and imaging core facilities Hands-on: Setting up an OMERO server in a virtual machine environment
Target audience: This workshop was directed at universities and research institutions who consider or plan to implement OMERO, or are in an early phase of implementation. This workshop was intended for teams from IT departments and imaging facilities to participate together with one person from the IT department, and one person from the imaging core facility at the same institution. The trainers:
Prof. Dr. Stefanie Weidtkamp-Peters (Imaging Core Facility Head, Center for Advanced Imaging, Heinrich Heine University of Düsseldorf) Dr. Susanne Kunis (Software architect, OMERO administrator, metadata specialist, University of Osnabrück) Dr. Tom Boissonnet (OMERO admin and image metadata specialist, Center for Advanced Imaging, Heinrich Heine University of Düsseldorf) Dr. Bettina Hagen (IT Administration and service specialist, Max Planck Institute for the Biology of Ageing, Cologne) Dr. Christian Schmidt (Science Manager for Research Data Management in Bioimaging, German Cancer Research Center (DKFZ), Heidelberg)
Time and place The format was a two-day, in-person workshop (October 16-17, 2024). Location: Heidelberg, Germany Workshop learning goals
Learn the steps to establish a local RDM environment fit for bioimaging data Create a network of IT experts and bioimaging specialists for bioimage RDM across institutions Establish a stakeholder process management for installing OMERO-based RDM Learn from each other, leverage different expertise Learn how to train users, establish sustainability strategies, and foster FAIR RDM for bioimaging at your institution
Tags: Nfdi4Bioimage, Research Data Management, Exclude From Dalia
[Workshop] Bioimage data management and analysis with OMERO#
Riccardo Massei, Michele Bortolomeazzi, Christian Schmidt
Published 2024-05-13
Licensed CC-BY-4.0
Here we share the material used in a workshop held on May 13th, 2024, at the German Cancer Research Center in Heidelberg (on-premise) Description:Microscopy experiments generate information-rich, multi-dimensional data, allowing us to investigate biological processes at high spatial and temporal resolution. Image processing and analysis is a standard procedure to retrieve quantitative information from biological imaging. Due to the complex nature of bioimaging files that often come in proprietary formats, it can be challenging to organize, structure, and annotate bioimaging data throughout a project. Data often needs to be moved between collaboration partners, transformed into open formats, processed with a variety of software tools, and exported to smaller-sized images for presentation. The path from image acquisition to final publication figures with quantitative results must be documented and reproducible. In this workshop, participants learn how to use OMERO to organize their data and enrich the bioimage data with structured metadata annotations.We also focus on image analysis workflows in combination with OMERO based on the Fiji/ImageJ software and using Jupyter Notebooks. In the last part, we explore how OMERO can be used to create publication figures and prepare bioimage data for publication in a suitable repository such as the Bioimage Archive. Module 1 (9 am - 10.15 am): Basics of OMERO, data structuring and annotation Module 2 (10.45 am - 12.45 pm): OMERO and Fiji Module 3 (1.45 pm - 3.45 pm): OMERO and Jupyter Notebooks Module 4 (4.15 pm - 6. pm): Publication-ready figures and data with OMERO The target group for this workshopThis workshop is directed at researchers at all career levels who plan to or have started to use OMERO for their microscopy research data management. We encourage the workshop participants to bring example data from their research to discuss suitable metadata annotation for their everyday practice. Prerequisites:Users should bring their laptops and have access to the internet through one of the following options:- eduroam- institutional WiFi- VPN connection to their institutional networks to access OMERO Who are the trainers? Dr. Riccardo Massei (Helmholtz-Center for Environmental Research, UFZ, Leipzig) - Data Steward for Bioimaging Data in NFDI4BIOIMAGE Dr. Michele Bortolomeazzi (DKFZ, Single cell Open Lab, bioimage data specialist, bioinformatician, staff scientist in the NFDI4BIOIMAGE project) Dr. Christian Schmidt (Science Manager for Research Data Management in Bioimaging, German Cancer Research Center, Heidelberg, Project Coordinator of the NFDI4BIOIMAGE project)
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
[Workshop] Managing FAIR microscopy data at scale for universities and research institutions: an introduction for non-imaging stakeholders#
Christian Schmidt, Michele Bortolomeazzi, Ksenia Krooß, Jan-Philipp Mallm, Elisa Ferrando-May, Stefanie Weidtkamp-Peters
Published 2025-03-14
Licensed CC-BY-4.0
These slides were used in a workshop at the 2025 E-Science Tage in Heidelberg. Workshop Abstract: Effective Research Data Management (RDM) requires collaboration between infrastructure providers, support units, and domain-specific experts across scientific disciplines. Microscopy, or bioimaging, is a widely used technology at universities and research institutions, generating large, multi-dimensional datasets. Scientists now routinely produce microscopy data using advanced imaging modalities, often through centrally-provided instruments maintained by core facilities. Bioimaging data management presents unique challenges: files are often large (e.g., 15+ GB for whole slide images), come in various proprietary formats, and are accessed frequently for viewing as well as for complex image processing and analysis workflows. Collaboration between experimenters, clinicians, group leaders, core facility staff, and image analysts adds to the complexity, increasing the risk of data fragmentation and metadata loss. The DFG-funded project I3D:bio and the consortium NFDI4BIOIMAGE, part of Germany’s National Research Data Infrastructure (NFDI), are addressing these challenges by developing solutions and best practices for managing large, complex microscopy datasets. This workshop introduces the challenges of bioimaging RDM to institutional support personnel, including, for example, library staff, IT departments, and data stewards. Participants will explore the bioimaging RDM system OMERO, and apply structured metadata annotation and object-oriented data organization to a simple training dataset. OMERO offers centralized, secure access to data, allowing collaboration and reducing the data fragementation risk. Moreover, participants will experience the benefits of OME-Zarr, a chunked open file format designed for FAIR data sharing and remote access. OME-Zarr enables streaming of large, N-dimensional array-typed data over the Internet without the need to download whole files. An expanding toolbox for leveraging OME-Zarr for bioimaging data renders this file type a promising candidate for a standard file format suitable for use in FAIR Digital Object (FDO) implementations for microscopy data. OME-Zarr has become a pillar for imaging data sharing in two bioimaging-specific data repositories, i.e., the Image Data Resource (IDR) and the BioImage Archive (BIA). The team of Data Stewards from both abovenmentioned projects help researchers and research support staff to manage und publish bioimaging data. By the end of the workshop, participants will have gained hands-on experience with bioimaging data and will be aware of support resources like the NFDI4BIOIMAGE Help Desk for addressing specific local use cases. Our goal is to promote collaboration across disciplines to effectively manage complex bioimaging data in compliance with the FAIR principles.
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
[Workshop] Research Data Management for Microscopy and BioImage Analysis#
Christian Schmidt, Tom Boissonnet, Michele Bortolomeazzi, Ksenia Krooß
Published 2024-09-30
Licensed CC-BY-4.0
Research Data Management for Microscopy and BioImage Analysis
Introduction to BioImaging Research Data Management, NFDI4BIOIMAGE and I3D:bioChristian Schmidt /DKFZ Heidelberg OMERO as a tool for bioimaging data managementTom Boissonnet /Heinrich-Heine Universität Düsseldorf Reproducible image analysis workflows with OMERO software APIsMichele Bortolomeazzi /DKFZ Heidelberg Publishing datasets in public archives for bioimage dataKsenia Krooß /Heinrich-Heine Universität Düsseldorf
Date & Venue:Thursday, Sept. 26, 5.30 p.m.Haus 22 / Paul Ehrlich Lecture Hall (H22-1)University Hospital Frankfurt
Tags: Nfdi4Bioimage, Research Data Management, Include In Dalia
dmtxSampleCreator#
SaibotMagd
Published 2023-06-06T11:52:14+00:00
Licensed APACHE-2.0
firefox extension: reads datamatrix code from camera and create a sample in an inventory to link it into an ELN.
Tags: Nfdi4Bioimage, Exclude From Dalia
Content type: Github Repository
ome2024-ngff-challenge#
Will Moore, Josh Moore, sherwoodf, Jean-Marie Burel, Norman Rzepka, dependabot[bot], JensWendt, Joost de Folter, Torsten St\xF6ter, AybukeKY, Eric Perlman, Tom Boissonnet
Published 2024-08-30T12:00:53+00:00
Licensed BSD-3-CLAUSE
Project planning and material repository for the 2024 challenge to generate 1 PB of OME-Zarr data
Tags: Sharing, Nfdi4Bioimage, Research Data Management, Exclude From Dalia
Content type: Github Repository