Poster (10)#

A study on long-term reproducibility of image analysis results on ImageJ and Fiji#

Robert Haase, Deborah Schmidt, Wayne Rasband, Curtis Rueden, Florian Jug, Pavel Tomancak, Eugene W. Myers

Tags: Imagej

Content type: Publication, Poster

https://figshare.com/articles/poster/I2K_Poster_Haase_V6_ImageJ_repro_pdf/7409525


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

https://zenodo.org/doi/10.5281/zenodo.8349562


Developing (semi)automatic analysis pipelines and technological solutions for metadata annotation and management in high-content screening (HCS) bioimaging#

Riccardo Massei, Stefan Scholz, Wibke Busch, Thomas Schnike, Hannes Bohring, Jan Bumberger

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

https://doi.org/10.5281/zenodo.8434325


EDAM-bioimaging - The ontology of bioimage informatics operations, topics, data, and formats#

Matúš Kalaš et al.

Licensed CC-BY-4.0

EDAM-bioimaging is an extension of the EDAM ontology, dedicated to bioimage analysis, bioimage informatics, and bioimaging.

Tags: Ontology, Bioimage Analysis

Content type: Poster

https://hal.science/hal-02267597/document


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: Metadata

Content type: Publication, Poster

https://f1000research.com/posters/9-162


NFDI4BIOIMAGE - An Initiative for a National Research Data Infrastructure for Microscopy Data#

Christian Schmidt, Elisa Ferrando-May

Licensed CC-BY-SA-4.0

Tags: Nfdi4Bioimage, Research Data Management

Content type: Poster, Publication

https://archiv.ub.uni-heidelberg.de/volltextserver/29489/


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

https://zenodo.org/doi/10.5281/zenodo.10730423


[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

https://zenodo.org/doi/10.5281/zenodo.8340247


[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

https://zenodo.org/doi/10.5281/zenodo.11235512


[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

https://zenodo.org/doi/10.5281/zenodo.7928332