Cc-by-4.0 (108)#
“ZENODO und Co.” Was bringt und wer braucht ein Repositorium?#
[‘Elfi Hesse’, ‘Jan-Christoph Deinert’, ‘Christian Löschen’]
Published 2021-01-25
Licensed CC-BY-4.0
Die Online-Veranstaltung fand am 21.01.2021 im Rahmen der SaxFDM-Veranstaltungsreihe “Digital Kitchen - Küchengespräche mit SaxFDM” statt. SaxFDM-Sprecherin Elfi Hesse (HTW Dresden) erläuterte zunächst Grundsätzliches zum Thema Repositorien. Anschließend teilten Nutzer (Jan Deinert – HZDR) und Anbieter (Christian Löschen – TU Dresden/ZIH) lokaler Repositorien ihre Erfahrungen mit uns.
Tags: Research Data Management
Content type: Slides
6 Steps Towards Reproducible Research#
[‘Heidi Seibold’]
Licensed CC-BY-4.0
A short book with 6 steps that get you closer to making your work reproducible.
Tags: Reproducibility, Research Data Management
Content type: Book
A Cloud-Optimized Storage for Interactive Access of Large Arrays#
[‘Josh Moore’, ‘Susanne Kunis’]
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Research Data Management
Content type: Publication, Conference Abstract
A Glimpse of the Open-Source FLIM Analysis Software Tools FLIMfit, FLUTE and napari-flim-phasor-plotter#
[‘Anca Margineanu’, ‘Chiara Stringari’, ‘Marcelo Zoccoler’, ‘Cornelia Wetzker’]
Licensed CC-BY-4.0
The presentations introduce open-source software to read in, visualize and analyse fluorescence lifetime imaging microscopy (FLIM) raw data developed for life scientists. The slides were presented at German Bioimaging (GerBI) FLIM Workshop held February 26 to 29 2024 at the Biomedical Center of LMU München by Anca Margineanu, Chiara Stringari and Conni Wetzker.
Tags: Bioimage Analysis, Flim
Content type: Slides
A Hitchhiker’s guide through the bio-image analysis software universe#
[‘Robert Haase’, ‘Elnaz Fazeli’, ‘David Legland’, ‘Michael Doube’, ‘Siân Culley’, ‘Ilya Belevich’, ‘Eija Jokitalo’, ‘Martin Schorb’, ‘Anna Klemm’, ‘Christian Tischer’]
Licensed CC-BY-4.0
This article gives an overview about commonly used bioimage analysis software and which aspects to consider when choosing a software for a specific project.
Tags: Bioimage Analysis
Content type: Publication
https://febs.onlinelibrary.wiley.com/doi/full/10.1002/1873-3468.14451
Alles meins – oder!? Urheberrechte klären für Forschungsdaten#
[‘Stephan Wünsche’]
Published 2024-06-04
Licensed CC-BY-4.0
Wem gehören Forschungsdaten? Diese Frage stellt sich bei Daten, an deren Entstehung mehrere Personen beteiligt waren, und besonders bei Textdaten, Bildern und Videos. Hier lernen Sie, für Ihr eigenes Forschungsvorhaben zu erkennen, wessen Urheber- und Leistungsschutzrechte zu berücksichtigen sind. Sie erfahren, wie Sie mit Hilfe von Vereinbarungen frühzeitig Rechtssicherheit herstellen, etwa um Daten weitergeben oder publizieren zu können.
Tags: Research Data Management, Licensing
Content type: Slides
BIDS-lecture-2024#
[‘Robert Haase’]
Licensed CC-BY-4.0
Training resources for Students at Uni Leipzig who want to dive into bio-image data science with Python. The material developed here between April and July 2024.
Tags: Bioimage Analysis, Deep Learning, Microscopy Image Analysis, Python
Content type: Github Repository
BigDataProcessor2: A free and open-source Fiji plugin for inspection and processing of TB sized image data#
[‘Christian Tischer’, ‘Ashis Ravindran’, ‘Sabine Reither’, ‘Nicolas Chiaruttini’, ‘Rainer Pepperkok’, ‘Nils Norlin’]
Licensed CC-BY-4.0
Tags: Research Data Management, Bioimage Analysis
Content type: Publication
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, Tu Dresden, Bioimage Data, Nfdi4Bioimage
Content type: Slide
Bio-image Analysis with the Help of Large Language Models#
[‘Robert Haase’]
Published 2024-03-13
Licensed CC-BY-4.0
Large Language Models (LLMs) change the way how we use computers. This also has impact on the bio-image analysis community. We can generate code that analyzes biomedical image data if we ask the right prompts. This talk outlines introduces basic principles, explains prompt engineering and how to apply it to bio-image analysis. We also compare how different LLM vendors perform on code generation tasks and which challenges are ahead for the bio-image analysis community.
Tags: Large Language Models, Python
Content type: Slide
Bio-image Data Science#
[‘Robert Haase’]
Licensed CC-BY-4.0
This repository contains training resources for Students at Uni Leipzig who want to dive into bio-image data science with Python.
Tags: Image Data Management, Deep Learning, Microscopy Image Analysis, Python
Content type: Notebook
Bio-image Data Science Lectures @ Uni Leipzig / ScaDS.AI#
[‘Robert Haase’]
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 developed here between April and July 2024.
Tags: Bioimage Analysis, Deep Learning, Microscopy Image Analysis, Python
Content type: Slides
Bio-image analysis, biostatistics, programming and machine learning for computational biology#
[‘Anna Poetsch’, ‘Biotec Dresden’, ‘Marcelo Leomil Zoccoler’, ‘Johannes Richard Müller’, ‘Robert Haase’]
Licensed CC-BY-4.0
Tags: Python, Bioimage Analysis, Napari
Content type: Notebook
Bio.tools database#
Licensed CC-BY-4.0
Tags: Bioinformatics
Content type: Collection
BioImage Analysis Notebooks#
[‘Robert Haase et al.’]
Licensed [‘CC-BY-4.0’, ‘BSD-3-CLAUSE’]
Tags: Python, Bioimage Analysis
Content type: Book, Notebook
https://haesleinhuepf.github.io/BioImageAnalysisNotebooks/intro.html
Browsing the Open Microscopy Image Data Resource with Python#
[‘Robert Haase’]
Licensed CC-BY-4.0
Tags: Omero, Python
Content type: Blog
https://biapol.github.io/blog/robert_haase/browsing_idr/readme.html
Challenges and opportunities for bio-image analysis core-facilities#
[‘Robert Haase’]
Licensed CC-BY-4.0
Tags: Research Data Management, Bio-Image Analysis, Nfdi4Bioimage
Content type: Slide
Challenges and opportunities for bioimage analysis core-facilities#
[‘Johannes Richard Soltwedel’, ‘Robert Haase’]
Licensed CC-BY-4.0
This article outlines common reasons for founding bioimage analysis core-facilities, services they can provide to fulfill certain need and conflicts of interest that arise from these services.
Tags: Bioimage Analysis, Research Data Management
Content type: Publication
ChatGPT for Image Analysis#
[‘Robert Haase’]
Published 2024-08-25
Licensed CC-BY-4.0
Large Language Models (LLMs) such as ChatGPT are changing the way we interact with computers, including how we analye microscopy imaging data. In this talk I introduce basic concepts of asking LLMs to write code and how to modify the questions to get the best out of it. For trying out these prompt engineering basics there are additional online resources available: https://scads.github.io/prompt-engineering-basics-2024/intro.html
Collaborative bio-image analysis script editing with git#
[‘Robert Haase’]
Licensed CC-BY-4.0
Introduction to version control using git for collaborative, reproducible script editing.
Tags: Sharing, Research Data Management
Content type: Blog
Combining the BIDS and ARC Directory Structures for Multimodal Research Data Organization#
[‘Torsten Stöter’, ‘Tobias Gottschall’, ‘Andrea Schrader’, ‘Peter Zentis’, ‘Monica Valencia-Schneider’, ‘Niraj Kandpal’, ‘Werner Zuschratter’, ‘Astrid Schauss’, ‘Timo Dickscheid’, ‘Timo Mühlhaus’, ‘Dirk von Suchodoletz’]
Licensed CC-BY-4.0
Interdisciplinary collaboration and integrating large, diverse datasets are crucial for answering complex research questions, requiring multimodal data analysis and adherence to FAIR principles. To address challenges in capturing the full research cycle and contextualizing data, DataPLANT developed the Annotated Research Context (ARC), while the neuroimaging community extended the Brain Imaging Data Structure (BIDS) for microscopic image data, both providing standardized, file system-based storage structures for organizing and sharing data with metadata.
Tags: Research Data Management, Fair-Principles
Content type: Poster
Crashkurs Forschungsdatenmanagement#
[‘Barbara Weiner’, ‘Stephan Wünsche’, ‘Stefan Kühne’, ‘Pia Voigt’, ‘Sebastian Frericks’, ‘Clemens Hoffmann’, ‘Romy Elze’, ‘Ronny Gey’]
Published 2020-04-30
Licensed CC-BY-4.0
Diese Präsentation bietet einen Einstieg in alle relevanten Bereiche des Forschungsdatenmanagements an der Universität Leipzig. Behandelt werden Grundlagen des Forschungsdatenmanagements, technische, ethische und rechtliche Aspekte sowie die Archivierung und Publikation von Forschungsdaten. Die Präsentation enthält zahlreiche weiterführende Links (rot) und Literaturhinweise.
Ergänzend hierzu wird eine Präsentation mit Übungsaufgaben angeboten, die helfen soll, das Gelernte zu festigen und in der eigenen Forschungspraxis umzusetzen. Den Aufgaben folgen jeweils eine Antwortfolie sowie deren Auflösung.
Tags: Research Data Management
Content type: Slides
Creating open computational curricula#
[‘Kari Jordan’, ‘Zhian Kamvar’, ‘Toby Hodges’]
Published 2020-12-11
Licensed CC-BY-4.0
In this interactive session, Carpentries team members will guide attendees through three stages of the backward design process to create a lesson development plan for the open source tool of their choosing. Attendees will leave having identified what practical skills they aim to teach (learning objectives), an approach for designing challenge questions (formative assessment), and mechanisms to give and receive feedback.
Content type: Slide
Cultivating Open Training#
[‘Robert Haase’]
Published 2024-03-14
Licensed CC-BY-4.0
In this SaxFDM Digital Kitchen, I introduced current challenges and potential solutions for openly sharing training materials, softly focusing on bio-image analysis. In this field a lot of training materials circulate in private channels, but openly shared, reusable materials, according to the FAIR-principles, are still rare. Using the CC-BY license and uploading materials to publicly acessible repositories are proposed to fill this gap.
Tags: Open Science, Research Data Management, Fair-Principles, Bio-Image Analysis, Licensing
Content type: Slides
Cultivating Open Training to advance Bio-image Analysis#
[‘Robert Haase’]
Published 2024-04-25
Licensed CC-BY-4.0
These slides introduce current challenges and potential solutions for openly sharing training materials, focusing on bio-image analysis. In this field a lot of training materials circulate in private channels, but openly shared, reusable materials, according to the FAIR-principles, are still rare. Using the CC-BY license and publicly acessible repositories are proposed to fill this gap.
Tags: Research Data Management, Licensing, Fair-Principles
Content type: Slides
DL4MicEverywhere#
[‘Iván Hidalgo’, ‘et al.’]
Licensed CC-BY-4.0
Content type: Notebook, Collection
Data Carpentry for Biologists#
Licensed [‘CC-BY-4.0’, ‘MIT’]
Content type: Tutorial, Code
Datenmanagement#
[‘Robert Haase’]
Published 2024-04-14
Licensed CC-BY-4.0
In dieser Data Management Session wird der Lebenszyklus von Daten näher beleuchtet. Wie entstehen Daten, was passiert mit ihnen, wenn sie verarbeitet werden? Wem gehören die Daten und wer ist dafür verantwortlich, sie zu veröffentlichen, zu archivieren und gegebenenfalls wiederzuverwenden? Wir werden einen Datenmanagementplan in Gruppenarbeit entwerfen, ggf. mit Hilfe von ChatGPT.
Tags: Research Data Management
Content type: Slides
Datenmanagement im Fokus: Organisation, Speicherstrategien und Datenschutz#
[‘Pia Voigt’, ‘Carolin Hundt’]
Published 2024-04-19
Licensed CC-BY-4.0
Workshop zum Thema „Datenmanagement im Fokus: Organisation, Speicherstrategien und Datenschutz“ auf der Data Week Leipzig Der Umgang mit Daten ist im Alltag nicht immer leicht: Wie und wo speichert man Daten idealerweise? Welche Strategien helfen, den Überblick zu behalten und wie geht man mit personenbezogenen Daten um? Diese Fragen möchten wir gemeinsam mit Ihnen anhand individueller Datenprobleme besprechen und Ihnen Lösungen aufzeigen, wie Sie ihr Datenmanagement effizient gestalten können.
Tags: Research Data Management
Content type: Slides
Datenmanagementpläne erstellen - Teil 1#
[‘Pia Voigt’, ‘Barbara Weiner’]
Published 2021-03-23
Licensed CC-BY-4.0
Was ist ein Datenmanagementplan? Welche Vorgaben sollte ich beachten? Wie erstelle ich einen solchen für mein Forschungsprojekt und welche nützlichen Tools kann ich hierfür verwenden?
Die Anforderungen der Forschungsförderer zum Datenmanagement steigen stetig. Damit verbunden ist häufig auch das Erstellen eines Datenmanagementplans. Dabei erwarten DFG, BMBF oder die EU jeweils unterschiedliche Angaben zur Erhebung, Speicherung und Veröffentlichung von projektbezogenen Forschungsdaten. Zudem bietet das Erstellen eines Datenmanagementplans viele Vorteile und hilft Ihnen nicht zuletzt, die Anforderungen der guten wissenschaftlichen Praxis strukturiert umzusetzen.
Was im ersten Moment unübersichtlich und überfordernd wirkt, soll in diesem Kurs anhand einer grundlegenden theoretischen Einführung im ersten und praxisorientierter Beispiele im zweiten Teil der Veranstaltung handhabbar gemacht werden. Sie lernen, was hinter den Anforderungen der Forschungsförderer steckt, welche Elemente ein Datenmanagementplan enthalten sollte und wie sie einen solchen mithilfe interaktiver Tools selbst erstellen können.
Tags: Research Data Management
Content type: Slides
Datenmanagementpläne erstellen - Teil 2#
[‘Pia Voigt’, ‘Barbara Weiner’]
Published 2021-03-30
Licensed CC-BY-4.0
Was ist ein Datenmanagementplan? Welche Vorgaben sollte ich beachten? Wie erstelle ich einen solchen für mein Forschungsprojekt und welche nützlichen Tools kann ich hierfür verwenden?
Die Anforderungen der Forschungsförderer zum Datenmanagement steigen stetig. Damit verbunden ist häufig auch das Erstellen eines Datenmanagementplans. Dabei erwarten DFG, BMBF oder die EU jeweils unterschiedliche Angaben zur Erhebung, Speicherung und Veröffentlichung von projektbezogenen Forschungsdaten. Zudem bietet das Erstellen eines Datenmanagementplans viele Vorteile und hilft Ihnen nicht zuletzt, die Anforderungen der guten wissenschaftlichen Praxis strukturiert umzusetzen.
Was im ersten Moment unübersichtlich und überfordernd wirkt, soll in diesem Kurs anhand einer grundlegenden theoretischen Einführung im ersten und praxisorientierter Beispiele im zweiten Teil der Veranstaltung handhabbar gemacht werden. Sie lernen, was hinter den Anforderungen der Forschungsförderer steckt, welche Elemente ein Datenmanagementplan enthalten sollte und wie sie einen solchen mithilfe interaktiver Tools selbst erstellen können.
Version 2 enthält aktuelle Links und weiterführende Hinweise zu einzelnen Aspekten eines Datenmanagementplans.
Version 3 ist die überarbeitete und aktualisierte Version der ersten beiden und enthält u.a. Hinweise zur Lizenzierung und zu Nutzungsrechten an Forschungsdaten.
Tags: Research Data Management
Content type: Slides
Developing (semi)automatic analysis pipelines and technological solutions for metadata annotation and management in high-content screening (HCS) bioimaging#
[‘Scholz Massei’, ‘Schnike Busch’, ‘Bumberger Bohring’]
Licensed CC-BY-4.0
High-content screening (HCS) bioimaging automates the imaging and analysis of numerous biological samples, generating extensive metadata that is crucial for effective image management and interpretation. Efficiently handling this complex data is essential to implementing FAIR principles and realizing HCS’s full potential for scientific discoveries.
Tags: Bioimage Analysis
Content type: Poster
Developing open-source software for bioimage analysis: opportunities and challenges#
[‘Florian Levet’, ‘Anne E. Carpenter’, ‘Kevin W. Eliceiri’, ‘Anna Kreshuk’, ‘Peter Bankhead’, ‘Robert Haase’]
Licensed CC-BY-4.0
This article outlines common challenges and practices when developing open-source software for bio-image analysis.
Tags: Neubias
Content type: Publication
EDAM-bioimaging: The ontology of bioimage informatics operations, topics, data, and formats (update 2020)#
[‘Matúš Kalaš’, ‘Laure Plantard’, ‘Joakim Lindblad’, ‘Martin Jones’, ‘Nataša Sladoje’, ‘Moritz A Kirschmann’, ‘Anatole Chessel’, ‘Leandro Scholz’, ‘Fabianne Rössler’, ‘Laura Nicolás Sáenz’, ‘Estibaliz Gómez de Mariscal’, ‘John Bogovic’, ‘Alexandre Dufour’, ‘Xavier Heiligenstein’, ‘Dominic Waithe’, ‘Marie-Charlotte Domart’, ‘Matthia Karreman’, ‘Raf Van de Plas’, ‘Robert Haase’, ‘David Hörl’, ‘Lassi Paavolainen’, ‘Ivana Vrhovac Madunić’, ‘Dean Karaica’, ‘Arrate Muñoz-Barrutia’, ‘Paula Sampaio’, ‘Daniel Sage’, ‘Sebastian Munck’, ‘Ofra Golani’, ‘Josh Moore’, ‘Florian Levet’, ‘Jon Ison’, ‘Alban Gaignard’, ‘Hervé Ménager’, ‘Chong Zhang’, ‘Kota Miura’, ‘Julien Colombelli’, ‘Perrine Paul-Gilloteaux’]
Licensed CC-BY-4.0
Tags: Meta Data
Content type: Publication, Poster
Efficiently starting institutional research data management#
[‘Katarzyna Biernacka’, ‘Katrin Cortez’, ‘Kerstin Helbig’]
Published 2019-10-15
Licensed CC-BY-4.0
Researchers are increasingly often confronted with research data management (RDM) topics during their work. Higher education institutions therefore begin to offer services for RDM at some point to give support and advice. However, many groundbreaking decisions have to be made at the very beginning of RDM services. Priorities must be set and policies formulated. Likewise, the staff must first be qualified in order to provide advice and adequately deal with the manifold problems awaiting. The FDMentor project has therefore bundled the expertise of five German universities with different experiences and levels of RDM knowledge to jointly develop strategies, roadmaps, guidelines, and open access training material. Humboldt-Universität zu Berlin, Freie Universität Berlin, Technische Universität Berlin, University of Potsdam, and European University Viadrina Frankfurt (Oder) have worked together on common solutions that are easy to adapt. With funding of the German Federal Ministry of Education and Research, the collaborative project addressed four problem areas: strategy development, legal issues, policy development, and competence enhancement. The aim of the project outcomes is to provide other higher education institutions with the best possible support for the efficient introduction of research data management. Therefore, all project results are freely accessible under the CC-BY 4.0 international license. The early involvement of the community in the form of workshops and the collection of feedback has proven its worth: the FDMentor strategies, roadmaps, guidelines, and training materials are applied and adapted beyond the partner universities.
Tags: Research Data Management
Content type: Document
Einblicke ins Forschungsdatenmanagement - Darf ich das veröffentlichen? Rechtsfragen im Umgang mit Forschungsdaten#
[‘Stephan Wünsche’, ‘Pia Voigt’]
Published 2021-05-11
Licensed CC-BY-4.0
Diese Präsentation wurde im Zuge der digitalen Veranstaltungsreihe “Einblicke ins Forschungsdatenmanagement” erstellt. Diese findet seit dem SS 2020 an der Universität Leipzig für alle Interessierten zu verschiedenen Themen des Forschungsdatenmanagements statt.
Dieser Teil der Reihe dreht sich um Rechtsfragen im Umgang mit Forschungsdaten und deren Bedeutung für die wissenschaftliche Praxis. Sie finden in der vorliegenden Präsentation einen Überblick über relevante Rechtsbereiche sowie Erläuterungen zum Datenschutz, Urheberrecht und den Grundsätzen der guten wissenschaftlichen Praxis mit Fokus auf deren Bedeutung im Forschungsdatenmanagement.
Tags: Research Data Management, Data Protection
Content type: Slides
Euro-BioImaging’s Guide to FAIR BioImage Data - Practical Tasks#
[‘Isabel Kemmer’, ‘Euro-BioImaging ERIC’]
Published 2024-06-04
Licensed CC-BY-4.0
Hands-on exercises on FAIR Bioimage Data from the interactive online workshop “Euro-BioImaging’s Guide to FAIR BioImage Data 2024” (https://www.eurobioimaging.eu/news/a-guide-to-fair-bioimage-data-2024/). Types of tasks included: FAIR characteristics of a real world dataset Data Management Plan (DMP) Journal Policies on FAIR data sharing Ontology search Metadata according to REMBI scheme (Image from: Sarkans, U., Chiu, W., Collinson, L. et al. REMBI: Recommended Metadata for Biological Images—enabling reuse of microscopy data in biology. Nat Methods 18, 1418–1422 (2021). https://doi.org/10.1038/s41592-021-01166-8) Matching datasets to bioimage repositories Browsing bioimage repositories
Tags: Bioimage Analysis, Fair-Principles, Research Data Management
Content type: Slides, Tutorial
Euro-BioImaging’s Template for Research Data Management Plans#
[‘Isabel Kemmer’, ‘Euro-BioImaging ERIC’]
Published 2024-06-04
Licensed CC-BY-4.0
Euro-BioImaging has developed a Data Management Plan (DMP) template with questions tailored to bioimaging research projects. Outlining data management practices in this way ensures traceability of project data, allowing for a continuous and unambiguous flow of information throughout the research project. This template can be used to satisfy the requirement to submit a DMP to certain funders. Regardless of the funder, Euro-BioImaging users are encouraged to provide a DMP and can use this template accordingly. This DMP template is available as a fillable PDF with further instructions and sample responses available by hovering over the fillable fields.
Tags: Bioimage Analysis, Fair-Principles, Research Data Management
Content type: Collection, Tutorial
FAIR BioImage Data#
Licensed CC-BY-4.0
Tags: Research Data Management, Fair, Bioimage Analysis
Content type: Collection, Video
https://www.youtube.com/watch?v=8zd4KTy-oYI&list=PLW-oxncaXRqU4XqduJzwFHvWLF06PvdVm
FAIRy deep-learning for bioImage analysis#
[‘Estibaliz Gómez de Mariscal’]
Licensed CC-BY-4.0
Introduction to FAIR deep learning. Furthermore, tools to deploy trained DL models (deepImageJ), easily train and evaluate them (ZeroCostDL4Mic and DeepBacs) ensure reproducibility (DL4MicEverywhere), and share this technology in an open-source and reproducible manner (BioImage Model Zoo) are introduced.
Tags: Deep Learning, Fair-Principles, Microscopy Image Analysis
Content type: Slides
Forschungsdaten.org#
Licensed CC-BY-4.0
Research Data Management Wiki in German
Tags: Research Data Management
Content type: Collection
Generative artificial intelligence for bio-image analysis#
[‘Robert Haase’]
Licensed CC-BY-4.0
Tags: Python, Bioimage Analysis, Artificial Intelligence
Content type: Slide
Getting started with Mambaforge and Python#
[‘Mara Lampert’]
Licensed CC-BY-4.0
Tags: Python, Conda, Mamba
Content type: Blog
https://biapol.github.io/blog/mara_lampert/getting_started_with_mambaforge_and_python/readme.html
Hackaton Results - Conversion of KNIME image analysis workflows to Galaxy#
[‘Riccardo Massei’]
Licensed CC-BY-4.0
Results of the project ‘Conversion of KNIME image analysis workflows to Galaxy’ during the Hackathon ‘Image Analysis in Galaxy’ (Freiburg 26 Feb - 01 Mar 2024)
Tags: Research Data Management
Content type: Slides
High throughput & automated data analysis and data management workflow with Cellprofiler and OMERO#
[‘Sarah Weischer’, ‘Jens Wendt’, ‘Thomas Zobel’]
Licensed CC-BY-4.0
In this workshop a fully integrated data analysis solutions employing OMERO and commonly applied image analysis tools (e.g., CellProfiler, Fiji) using existing python interfaces (OMERO Python language bindings, ezOmero, Cellprofiler Python API) is presented.
Tags: Omero, Data Analysis, Bioimage Analysis
Content type: Collection
Highlights from the 2016-2020 NEUBIAS training schools for Bioimage Analysts: a success story and key asset for analysts and life scientists#
[‘Gabriel G. Martins’, ‘Fabrice P. Cordelières’, ‘Julien Colombelli’, ‘Rocco D’Antuono’, ‘Ofra Golani’, ‘Romain Guiet’, ‘Robert Haase’, ‘Anna H. Klemm’, ‘Marion Louveaux’, ‘Perrine Paul-Gilloteaux’, ‘Jean-Yves Tinevez’, ‘Kota Miura’]
Published 2021
Licensed CC-BY-4.0
Tags: Bioimage Analysis, Neubias
Content type: Publication
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
Content type: Slide, Video
https://zenodo.org/records/8323588
https://www.youtube.com/playlist?list=PL2k-L-zWPoR7SHjG1HhDIwLZj0MB_stlU
If you license it, it’ll be harder to steal it. Why we should license our work#
[‘Robert Haase’]
Licensed CC-BY-4.0
Blog post about why we should license our work and what is important when choosing a license.
Tags: Licensing, Research Data Management
Content type: Blog
Image Analysis Training Resources#
Licensed CC-BY-4.0
Tags: Neubias, Bioimage Analysis
Content type: Book
Image Processing with Python#
[‘Jacob Deppen’, ‘Kimberly Meechan’, ‘David Palmquist’, ‘Ulf Schiller’, ‘Robert Turner’, ‘Marianne Corvellec’, ‘Toby Hodges’, ‘et al.’]
Licensed CC-BY-4.0
Content type: Python, Bioimage Analysis
Insights and Impact From Five Cycles of Essential Open Source Software for Science#
[‘Kate Hertweck’, ‘Carly Strasser’, ‘Dario Taraborelli’]
Licensed CC-BY-4.0
Open source software (OSS) is essential for advancing scientific discovery, particularly in biomedical research, yet funding to support these vital tools has been limited. The Chan Zuckerberg Initiative’s Essential Open Source Software for Science (EOSS) program has significantly contributed to this field by providing $51.8 million in funding over five years to support the maintenance, growth, and community engagement of critical OSS tools. The program has impacted scientific OSS projects by improving their technical outputs, community building, and sustainability practices, and fostering collaborations within the OSS community. Additionally, EOSS funding has enhanced diversity, equity, and inclusion within the OSS community, although changes in principal investigator demographics were not observed. The funded projects have had a substantial impact on biomedical research by improving the usability and accessibility of scientific software, which has led to increased adoption and advancements in various biomedical fields.
Tags: Open Source Software, Funding, Sustainability
Content type: Report
Introduction to Bioimage Analysis#
[‘Pete Bankhead’]
Licensed CC-BY-4.0
Tags: Python, Imagej, Bioimage Analysis
Content type: Book, Notebook
Kollaboratives Arbeiten und Versionskontrolle mit Git#
[‘Robert Haase’]
Published 2024-04-15
Licensed CC-BY-4.0
Gemeinsames Arbeiten im Internet stellt uns vor neue Herausforderungen: Wer hat eine Datei wann hochgeladen? Wer hat zum Inhalt beigetragen? Wie kann man Inhalte zusammenfuehren, wenn mehrere Mitarbeiter gleichzeitig Aenderungen gemacht haben? Das Versionskontrollwerkzeug git stellt eine umfassende Loesung fuer solche Fragen bereit. Die Onlineplatform github.com stellt nicht nur Softwareentwicklern weltweit eine git-getriebene Platform zur Verfuegung und erlaubt ihnen effektiv zusammen zu arbeiten. In diesem Workshop lernen wir:
Infuerung in FAIR-Prinzipien im Softwarecontext Arbeiten mit git: Pull-requests Aufloesen von Merge-Konflikten Automatisiertes Archivieren von Inhalten nach Zenodo.org Eigene Webseiten auf github.io publizieren
Tags: Research Data Management, Fair-Principles, Git, Zenodo
Content type: Slides
Large Language Models: An Introduction for Life Scientists#
[‘Robert Haase’]
Published 2024-08-27
Licensed CC-BY-4.0
Large Language Models (LLMs) are changing the way how humans interact with computers. This has impact on all scientific fields by enabling new ways to achieve for example data analysis goals. In this talk we will go through an introduction to LLMs with respect to applications in the life sciences, focusing on bio-image analysis. We will see how to generate text and images using LLMs and how LLMs can extract information from reproducibly images through code-generation. We will go through selected prompt engineering techniques enabling scientists to tune the output of LLMs towards their scientific goal and how to do quality assurance in this context.
Making your package available on conda-forge#
[‘Kevin Yamauchi’]
Licensed CC-BY-4.0
Tags: Deployment, Python
Content type: Documentation
https://kevinyamauchi.github.io/open-image-data/how_tos/conda_forge_packaging.html
Managing Scientific Python environments using Conda, Mamba and friends#
[‘Robert Haase’]
Licensed CC-BY-4.0
Tags: Python, Conda, Mamba
Content type: Blog
Meeting in the Middle: Towards Successful Multidisciplinary Bioimage Analysis Collaboration#
[‘Anjalie Schlaeppi’, ‘Wilson Adams’, ‘Robert Haase’, ‘Jan Huisken’, ‘Ryan B. MacDonald’, ‘Kevin W. Eliceiri’, ‘Elisabeth C. Kugler’]
Licensed CC-BY-4.0
Tags: Bioimage Analysis
Content type: Publication
https://www.frontiersin.org/articles/10.3389/fbinf.2022.889755/full
Methods in bioimage analysis#
[‘Christian Tischer’]
Licensed CC-BY-4.0
Tags: Bioimage Analysis
Content type: Online Tutorial, Video, Slide
https://www.ebi.ac.uk/training/events/methods-bioimage-analysis/
https://doi.org/10.6019/TOL.BioImageAnalysis22-w.2022.00001.1
https://drive.google.com/file/d/1MhuqfKhZcYu3bchWMqogIybKjamU5Msg/view
MicroSam-Talks#
[‘Constantin Pape’]
Published 2024-05-23
Licensed CC-BY-4.0
Talks about Segment Anything for Microscopy: computational-cell-analytics/micro-sam. Currently contains slides for two talks:
Overview of Segment Anythign for Microscopy given at the SWISSBIAS online meeting in April 2024 Talk about vision foundation models and Segment Anything for Microscopy given at Human Technopole as part of the EMBO Deep Learning Course in May 2024
Tags: Image Segmentation, Bio-Image Analysis, Deep Learning
Content type: Slides
Microscopy data analysis: machine learning and the BioImage Archive#
[‘Andrii Iudin’, ‘Anna Foix-Romero’, ‘Anna Kreshuk’, ‘Awais Athar’, ‘Beth Cimini’, ‘Dominik Kutra’, ‘Estibalis Gomez de Mariscal’, ‘Frances Wong’, ‘Guillaume Jacquemet’, ‘Kedar Narayan’, ‘Martin Weigert’, ‘Nodar Gogoberidze’, ‘Osman Salih’, ‘Petr Walczysko’, ‘Ryan Conrad’, ‘Simone Weyend’, ‘Sriram Sundar Somasundharam’, ‘Suganya Sivagurunathan’, ‘Ugis Sarkans’]
Licensed CC-BY-4.0
The Microscopy data analysis: machine learning and the BioImage Archive course, which focused on introducing programmatic approaches used in the analysis of bioimage data via the BioImage Archive, ran in May 2023.
Tags: Microscopy Image Analysis, Python, Deep Learning
Content type: Videos, Practicals, Slides
My Journey Through Bioimage Analysis Teaching Methods From Classroom to Cloud#
[‘Elnaz Fazeli’]
Published 2024-02-19
Licensed CC-BY-4.0
In these slides I introducemy journey through teaching bioimage analysis courses in different formats, from in person courses to online material. I have an overview of different training formats and comparing these for different audiences.
Tags: Teaching
Content type: Slides
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
Content type: 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
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
Content type: Slides
NFDI4BIOIMAGE - National Research Data Infrastructure for Microscopy and Bioimage Analysis#
[‘Marcelo Zoccoler’]
Published 2024-08-07
Licensed CC-BY-4.0
Bioimaging refers to a collection of methods to visualize the internal structures and mechanisms of living organisms. The fundamental tool, the microscope, has enabled seminal discoveries like that of the cell as the smallest unit of life, and continues to expand our understanding of biological processes. Today, we can follow the interaction of single molecules within nanoseconds in a living cell, and the development of complete small organisms like fish and flies over several days starting from the fertilized egg. Each image pixel encodes multiple spatiotemporal and spectral dimensions, compounding the massive volume and complexity of bioimage data. Proper handling of this data is indispensable for analysis and its lack has become a growing hindrance for the many disciplines of the life and biomedical sciences relying on bioimaging. No single domain has the expertise to tackle this bottleneck alone. As a method-specific consortium, NFDI4BIOMAGE seeks to address these issues, enabling bioimaging data to be shared and re-used like they are acquired, i.e., independently of disciplinary boundaries. We will provide solutions for exploiting the full information content of bioimage data and enable new discoveries through sharing and re-analysis. Our RDM strategy is based on a robust needs analysis that derives not only from a community survey but also from over a decade of experience in German BioImaging, the German Society for Microscopy and Image Analysis. It considers the entire lifecycle of bioimaging data, from acquisition to archiving, including analysis and enabling re-use. A foundational element of this strategy is the definition of a common, cloud-compatible, and interoperable digital object that bundles binary images with their descriptive and provenance metadata. With members from plant biology to neuroscience, NFDI4BIOIMAGE will champion the standardization of bioimage data to create a framework that answers discipline-specific needs while ensuring communication and interoperability with data types and RDM systems across domains. Integration of bioimage data with, e.g., omics data as the basis for spatial omics, holds great promise for fields such as cancer medicine. Unlocking the full potential of bioimage data will rely on the development and broad availability of exceptional analysis tools and training sets. NFDI4BIOIMAGE will make these accessible and usable including cutting-edge AI-based methods in scalable cloud environments. NFDI4BIOIMAGE intersects with multiple NFDI consortia, most prominently with GHGA for linking image and genomics data and with DataPLANT on the definition of FAIR data objects. Last but not least, NFDI4BIOIMAGE is internationally well connected and represents the opportunity for German scientists to keep path with and have a voice in several international initiatives focusing on the FAIRification of bioimage data as one of the main challenges for the advancement of knowledge in the life and biomedical sciences.
NFDI4BIOIMAGE: Perspective for a national bioimaging standard#
[‘Josh Moore’, ‘Susanne Kunis’]
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage
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
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
Content type: Github Repository
Nextflow: Scalable and reproducible scientific workflows#
[‘Floden Evan’, ‘Di Tommaso Paolo’]
Published 2020-12-17
Licensed CC-BY-4.0
Nextflow is an open-source workflow management system that prioritizes portability and reproducibility. It enables users to develop and seamlessly scale genomics workflows locally, on HPC clusters, or in major cloud providers’ infrastructures. Developed since 2014 and backed by a fast-growing community, the Nextflow ecosystem is made up of users and developers across academia, government and industry. It counts over 1M downloads and over 10K users worldwide.
Tags: Workflow Engine
Content type: Slide
OME Documentation#
Licensed CC-BY-4.0
Tags: Omero
Content type: Documentation
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
Content type: Publication
Open Image Data Handbook#
[‘Kevin Yamauchi’]
Licensed CC-BY-4.0
Tags: Neubias, Research Data Management, Napari, Python, Bioimage Analysis
Content type: Book, Notebook
Open Science, Sharing & Licensing#
[‘Robert Haase’]
Published 2024-04-18
Licensed CC-BY-4.0
Wir tauchen ein in die Welt der Open Science und definieren Begriffe wie Open Source, Open Access und die FAIR-Prinzipien (Findable, Accessible, Interoperable and Reuasable). Wir diskutieren, wie diese Methoden der [wissenschaftlichen] Kommunikation und des Datenmanagements die Welt verändern und wie wir sie praktisch in unsere Arbeit integrieren können. Dabei spielen Aspekte wie Copyright und Lizenzierung eine wichtige Rolle.
Tags: Research Data Management, Open Access, Fair-Principles, Licensing
Content type: Slides
Parallelization and heterogeneous computing: from pure CPU to GPU-accelerated image processing#
[‘Robert Haase’]
Licensed CC-BY-4.0
Content type: Slide
Photonic data analysis in 2050#
[‘Oleg Ryabchykov’, ‘Shuxia Guo’, ‘Thomas Bocklitz’]
Licensed CC-BY-4.0
Photonic data analysis, combining imaging, spectroscopy, machine learning, and computer science, requires flexible methods and interdisciplinary collaborations to advance. Essential developments include standardizing data infrastructure for comparability, optimizing data-driven models for complex investigations, and creating techniques to handle limited or unbalanced data and device variations.
Tags: Fair-Principles, Machine Learning, Research Data Management
Content type: Publication
PoL Bio-Image Analysis Training School on GPU-Accelerated Image Analysis#
[‘Stephane Rigaud’, ‘Brian Northan’, ‘Till Korten’, ‘Neringa Jurenaite’, ‘Apurv Deepak Kulkarni’, ‘Peter Steinbach’, ‘Sebastian Starke’, ‘Johannes Soltwedel’, ‘Marvin Albert’, ‘Robert Haase’]
Licensed CC-BY-4.0
This repository hosts notebooks, information and data for the GPU-Accelerated Image Analysis Track of the PoL Bio-Image Analysis Symposium.
Tags: Gpu, Clesperanto, Dask, Python
Content type: Notebook
BiAPoL/PoL-BioImage-Analysis-TS-GPU-Accelerated-Image-Analysis
Practical Guide to the International Alignment of Research Data Management - Extended Edition#
Licensed CC-BY-4.0
Content type: Book
QI 2024 Analysis Lab Manual#
[‘Beth Cimini’, ‘Florian Jug’, ‘QI 2024’]
Licensed CC-BY-4.0
This book contains the quantitative analysis labs for the QI CSHL course, 2024
Tags: Segmentation, Python
Content type: Notebook
https://bethac07.github.io/qi_2024_analysis_lab_manual/intro.html
QM Course Lectures on Bio-Image Analysis with napari 2024#
[‘Marcelo Leomil Zoccoler’]
Licensed CC-BY-4.0
In these lectures, we will explore ways to analyze microscopy images with Python and visualize them with napari, an nD viewer open-source software. The analysis will be done in Python mostly using the scikit-image, pyclesperanto and apoc libraries, via Jupyter notebooks. We will also explore some napari plugins as an interactive and convenient alternative way of performing these analysis, especially the napari-assistant, napari-apoc and napari-flim-phasor-plotter plugins.
Tags: Napari, Python
Content type: Notebook
https://zoccoler.github.io/QM_Course_Bio_Image_Analysis_with_napari_2024
QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy#
[‘Glyn Nelson’, ‘Ulrike Boehme’, ‘et al.’]
Licensed CC-BY-4.0
Tags: Quareo-Limi
Content type: Publication
QuPath: Open source software for analysing (awkward) images#
[‘Peter Bankhead’]
Published 2020-12-16
Licensed CC-BY-4.0
Slides from the CZI/EOSS online meeting in December 2020.
Tags: Bioimage Analysis
Content type: Slide
RDF as a bridge to domain-platforms like OMERO, or There and back again.#
[‘Josh Moore’, ‘Andra Waagmeester’, ‘Kristina Hettne’, ‘Katherine Wolstencroft’, ‘Susanne Kunis’]
Licensed CC-BY-4.0
In 2005, the first version of OMERO stored RDF natively. However, just a year after the 1.0 release of RDF, performance considerations led to the development of a more traditional SQL approach for OMERO. A binary protocol makes it possible to query and retrieve metadata but the resulting information cannot immediately be combined with other sources. This is the adventure of rediscovering the benefit of RDF triples as a – if not the – common exchange mechanism.
Tags: Research Data Management, Fair-Principles, Bioimage Analysis
Content type: Slides
RDM4Mic Presentations#
Licensed CC-BY-4.0
Tags: Research Data Management
Content type: Collection
RDMKit Training Resources#
Licensed CC-BY-4.0
Tags: Research Data Management
Content type: Collection
Research Data Management Seminar - Slides#
[‘Della Chiesa’, ‘Stefano’]
Published 2022-05-18
Licensed CC-BY-4.0
This Research Data Management (RDM) Slides introduce to the multidisciplinary knowledge and competencies required to address policy compliance and research data management best practices throughout a project lifecycle, and beyond it.
Module 1 - Introduces the RDM giving its context in the Research Data Governance
Module 2 - Illustrates the most important RDM policies and principles
Module 3 - Provides the most relevant RDM knowledge bricks
Module 4 - Discuss the Data Management Plans (DMPs), examples, templates and guidance
Tags: Research Data Management
Content type: Slide
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
Content type: Publication
Running Deep-Learning Scripts in the BiA-PoL Omero Server#
[‘Marcelo Zoccoler’]
Licensed CC-BY-4.0
Tags: Python, Artificial Intelligence, Bioimage Analysis
Content type: Blog
https://biapol.github.io/blog/marcelo_zoccoler/omero_scripts/readme.html
So geschlossen wie nötig, so offen wie möglich - Datenschutz beim Umgang mit Forschungsdaten#
[‘Pia Voigt’]
Published 2024-05-30
Licensed CC-BY-4.0
Der Umgang mit personenbezogenen Daten stellt Forschende oft vor rechtliche Herausforderungen: Unter welchen Bedingungen dürfen personenbezogene Daten verarbeitet werden? Welche Voraussetzungen müssen erfüllt sein und welche Strategien können angewendet werden, um Daten sicher speichern, verarbeiten, teilen und aufbewahren zu können? Mit Hilfe dieses Foliensatzes erhalten Sie Einblicke in datenschutzrechtliche Aspekte beim Umgang mit Ihren Forschungsdaten.
Tags: Research Data Management, Data Protection, Fair-Principles
Content type: Slides
SpatialData: an open and universal data framework for spatial omics#
[‘Luca Marconato’, ‘Giovanni Palla’, ‘Kevin A Yamauchi’, ‘Isaac Virshup’, ‘Elyas Heidari’, ‘Tim Treis’, ‘Marcella Toth’, ‘Rahul Shrestha’, ‘Harald Vöhringer’, ‘Wolfgang Huber’, ‘Moritz Gerstung’, ‘Josh Moore’, ‘Fabian J Theis’, ‘Oliver Stegle’]
Licensed CC-BY-4.0
Tags: Python
Content type: Publication, Preprint
https://www.biorxiv.org/content/10.1101/2023.05.05.539647v1.abstract
Structuring of Data and Metadata in Bioimaging: Concepts and technical Solutions in the Context of Linked Data#
[‘Susanne Kunis’]
Published 2022-08-24
Licensed CC-BY-4.0
guided walkthrough of poster at https://doi.org/10.5281/zenodo.6821815
which provides an overview of contexts, frameworks, and models from the world of bioimage data as well as metadata and the techniques for structuring this data as Linked Data.
You can also watch the video in the browser on the I3D:bio website.
Tags: Nfdi4Bioimage, Research Data Management
Content type: Video
Sustainable Data Stewardship#
[‘Stefano Della Chiesa’]
Published 2024-03-25
Licensed CC-BY-4.0
These slides were presented at the 2. SaxFDM-Beratungsstammtisch and delve into the strategic integration of Research Data Management (RDM) within research organizations. The Leibniz IOER presented an insightful overview of RDM activities and approaches, emphasizing the criticality of embedding RDM strategically within research institutions. The presentation showcases some best practices in RDM implementation through practical examples, offering valuable insights for optimizing data stewardship processes.
Tags: Research Data Management, Data Stewardship
Content type: Slides
The Turing Way: Guide for reproducible research#
Licensed [‘CC-BY-4.0’, ‘MIT’]
A guide which covers topics related to skills, tools and best practices for research reproducibility.
Content type: Book
https://the-turing-way.netlify.app/reproducible-research/reproducible-research
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
Content type: Slides
Towards Preservation of Life Science Data with NFDI4BIOIMAGE#
[‘Robert Haase’]
Published 2024-08-29
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.
Train-the-Trainer Concept on Research Data Management#
[‘Katarzyna Biernacka’, ‘Maik Bierwirth’, ‘Petra Buchholz’, ‘Dominika Dolzycka’, ‘Kerstin Helbig’, ‘Janna Neumann’, ‘Carolin Odebrecht’, ‘Cord Wiljes’, ‘Ulrike Wuttke’]
Published 2020-11-04
Licensed CC-BY-4.0
Within the project FDMentor, a German Train-the-Trainer Programme on Research Data Management (RDM) was developed and piloted in a series of workshops. The topics cover many aspects of research data management, such as data management plans and the publication of research data, as well as didactic units on learning concepts, workshop design and a range of didactic methods.
After the end of the project, the concept was supplemented and updated by members of the Sub-Working Group Training/Further Education (UAG Schulungen/Fortbildungen) of the DINI/nestor Working Group Research Data (DINI/nestor-AG Forschungsdaten). The newly published English version of the Train-the-Trainer Concept contains the translated concept, the materials and all methods of the Train-the-Trainer Programme. Furthermore, additional English references and materials complement this version.
Tags: Research Data Management
Content type: Book
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
Content type: Slides
Who you gonna call? - Data Stewards to the rescue#
[‘Vanessa Fuchs’, ‘Aphaia Fiona’, ‘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
Content type: Poster
[CORDI 2023] Zarr: A Cloud-Optimized Storage for Interactive Access of Large Arrays#
[‘Josh Moore’]
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: Research Data Management, Bioimage Analysis, Data Science
Content type: Poster
[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
Content type: Poster
[GBI EOE VII] Five (or ten) must-have items for making IT infrastructure for managing bioimage data#
[‘Josh Moore’]
Published 2024-05-26
Licensed CC-BY-4.0
Presentation made to the GBI Image Data Management Working Group during the 7th Exchange of Experience in Uruguay.
[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: Research Data Management
Content type: Slides
[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
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
Content type: Slides
[Workshop] FAIR data handling for microscopy: Structured metadata annotation in OMERO#
[‘Vanessa Fuchs’, ‘Fiona Aphaia’, ‘Christian Schmidt’, ‘Tom Boissonnet’]
Licensed CC-BY-4.0
How to optimize microscopy data management using structured metadata annotations in OMERO, facilitating organization for processing, analysis, and eventual publication. The focus lies on enhancing data findability and usability through object-oriented organization, integrating OMERO with ImageJ/Fiji for image analysis, and implementing community-accepted metadata standards like REMBI to ensure data reproducibility and reusability.
Tags: Research Data Management, Bioimage Analysis, Omero
Content type: Slides
ilastik: interactive machine learning for (bio)image analysis#
[‘Anna Kreshuk’, ‘Dominik Kutra’]
Licensed CC-BY-4.0
Tags: Artificial Intelligence, Bioimage Analysis
Content type: Slide
https://zenodo.org/doi/10.5281/zenodo.4330625