docs: document OME-Zarr for particular scientific modalities

resources/topic-hub/cryo-et/index.md

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+(topic-cryo-et)=
+
+# Cryo-ET
+
+Cryogenic electron tomography (cryo-ET) sits between single particle cryo-EM and volume EM. Cryo-ET involves the collection of tilt series of images from vitrified samples, which are then computationally reconstructed into 3D volumes.
+
+Here are some resources in the intersection of cryo-ET and OME-Zarr.
+
+## Tools
+
+- [ChimeraX OME-Zarr](https://github.com/uermel/chimerax-ome-zarr) - A plugin for [ChimeraX](https://www.cgl.ucsf.edu/chimerax/) to read and visualize OME-Zarr datasets designed for cryo-ET data.
+
+- [copick](https://copick.github.io/copick/) - CryoET annotation framework built upon OME-Zarr data. [[paper](https://onlinelibrary.wiley.com/doi/10.1002/pro.70578)]
+
+- [zarr-particle-tools](https://github.com/czimaginginstitute/zarr-particle-tools) - CryoET data analysis package (subtomogram averaging) based on OME-Zarr
+
+## Data
+
+- [Cryo-ET Data Portal](https://cryoetdataportal.czscience.com/) - Cryo-ET data portal, with datasets shared as OME-Zarr (arguably EM and volumetric, but usually not considered 'volume EM' in the sense of serial sectioning or block-face imaging). [[paper](https://www.nature.com/articles/s41592-024-02477-2)]
+
+## Other
+
+- [Cryo-ET Object Identification Kaggle Challenge](https://www.kaggle.com/competitions/czii-cryo-et-object-identification) - Kaggle competition for cryo-ET object identification, with OME-Zarr datasets.

resources/topic-hub/dynamics/index.md

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+(topic-dynamics)=
+
+# Dynamics
+
+OME-Zarr aids large-scale analysis of big data for dynamic processes, e.g. in 5D settings (volumetric, multi-channel time-lapses).
+
+Here are some resources related to dynamic (i.e. over time) imaging data that take benefit of OME-Zarr and the NGFF.
+
+## Biohub
+
+- [Dynamic Cell Atlas](https://chanzuckerberg.github.io/dynamic-cell-atlas-specs/index.html) - A specification for storing dynamic cell atlas data internal to Biohub, building upon OME-Zarr.
+
+- [Zebrahub – Multimodal Zebrafish Developmental Atlas Reveals the State-Transition Dynamics of Late-Vertebrate Pluripotent Axial Progenitors](https://www.biorxiv.org/content/10.1101/2023.03.06.531398v2) – Data at [Zebrahub Lightsheet Imaging Atlas](https://zebrahub.sf.czbiohub.org/imaging)

resources/topic-hub/hcs/index.md

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+(topic-hcs)=
+
+# High Content Screening
+
+High Content Screening (HCS) workflows record images for multiple conditions at the same time, often in multi-well plates. The OME-TIFF specification provided first-class support for HCS, and the OME-Zarr addressed HCS needs early on, with a [dedicated specification for plates and wells](https://ngff.openmicroscopy.org/0.5/#hcs-layout).
+
+- The [Fractal analytics framework](https://fractal-analytics-platform.github.io/) for large scale processing with OME-Zarr has multiple [workflows to analyse HCS data](https://fractal-analytics-platform.github.io/fractal_tasks/) ([preprint](https://www.biorxiv.org/content/10.64898/2026.03.05.709921v1.full)).
+
+- Massei, R., Busch, W., Serrano-Solano, B. et al. High-content screening (HCS) workflows for FAIR image data management with OMERO. Sci Rep 15, 16236 (2025). https://doi.org/10.1038/s41598-025-00720-0

resources/topic-hub/index.md

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+(topic-hub)=
+
+# Topic Hub
+
+The Topic Hub is a collection of resources particular to the intersection of NGFF and particular topical communities.
+
+It includes topics like "Whole Slide Imaging", "Volume EM", "Spatial Omics", and "Dynamics", for which a collection of links is provided, in a sort of [web directory](https://en.wikipedia.org/wiki/Web_directory) style:
+
+- [Volume EM](#topic-volume-em)
+- [Cryo-ET](#topic-cryo-et)
+- [High-Content Screening](#topic-hcs)
+- [Whole Slide Imaging](#topic-wsi)
+- [Spatial Omics](#topic-spatial-omics)
+- [Dynamics](#topic-dynamics)
+- [Tomography](#topic-tomography)

resources/topic-hub/spatial-omics/index.md

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+(topic-spatial-omics)=
+
+# Spatial Omics
+
+The SpatialData format builds upon OME-Zarr to provide a standard for storing spatial omics data. There are a number of resources that build either on OME-Zarr directly or upon SpatialData.
+
+## Spatial proteomics
+
+### spora ecosystem
+A suite of resources for spatial proteomics that use OME-Zarr at multiple levels. Includes:
+
+* [A spora data formats specification](https://spora.epfl.ch/docs-data.html) used to harmonize datasets.
+
+In short, it stores structured tabular data as `.parquet`, all whole-slide images as `.ome.zarr`, and  segmentation masks as `.npz`.
+
+* [spora[data]](https://spora.epfl.ch/datasets.html) a resource containing multiple harmonized spatial proteomics datasets
+* [spora [io]](https://github.com/bunnelab/spora-io) a Python library for accessing spora datasets
+* Wenckstern, J., Jain, E., von Querfurth, B. et al. The Virtual Tissues foundation model resolves spatial proteomics across scales. Nature (2026). https://doi.org/10.1038/s41586-026-10884-y ([github repo](https://github.com/bunnelab/virtues#datasets))
+
+## other
+
+- Meyer-Bender, M., Vöhringer, H., Schniederjohann, C. et al. Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data. Nat Methods (2026). https://doi.org/10.1038/s41592-026-03155-1
+
+An xarray/zarr Python toolkit for multiplexed immunofluorescence, using SpatialData for the underlying data representation, in connection with the [scverse ecosystem](https://scverse.org/).
+
+- Alexander Coulton, Nicholas McGranahan, Odon: an ultra-fast viewer for spatial proteomics, Bioinformatics, Volume 42, Issue 7, July 2026, btag514, https://doi.org/10.1093/bioinformatics/btag514
+
+A viewer for spatial proteomics data built directly for OME-Zarr datasets, with secondary support for SpatialData.

resources/topic-hub/tomography/index.md

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+(topic-tomography)=
+
+# Computed Tomography (CT)
+
+While the OME community comes from the bioimaging and microscopy world, the OME-NGFF specification is also applicable to other imaging modalities. There are several kinds of tomography that can benefit from the OME-NGFF specification, including x-ray computed tomography (CT-scan).
+
+The value of the specification includes the metadata for mapping voxels to physical space, and the ability to store large datasets in a chunked and compressed format, with multiscale support, that is suitable for cloud storage and analysis.
+
+## Example
+
+<iframe src="https://volumeviewer.allencell.org/viewer?url=https://ome-zarr-scivis.s3.us-east-1.amazonaws.com/v0.5/96x0/stag_beetle.ome.zarr" width="100%" height="600px" style="border: none;"></iframe>
+
+## Datasets
+
+- [The Human Organ Atlas](https://human-organ-atlas.esrf.fr/) - Human organs scanned with Hierarchical Phase-Contrast Tomography (HiP-CT) made available in the OME-Zarr format ([paper](https://www.science.org/doi/10.1126/sciadv.adz2240)).
+
+- [Herculaneum Scrolls](https://scrollprize.org/) - Scrolls carbonized by Mount Vesuvius eruptions imaged via X-ray micro-CT, made available in OME-Zarr format. ([data](https://registry.opendata.aws/vesuvius-challenge-herculaneum-scrolls/), [source](https://github.com/ScrollPrize/open-data)). Multimillion-dollar awards for teams that "unroll" the scrolls – all starting with processing OME-Zarr data.
+
+- [Open SciVis](https://registry.opendata.aws/ome-zarr-open-scivis/) - A collection of volumetric datasets in OME-Zarr format, including several CT scans. ([source](https://github.com/InsightSoftwareConsortium/OMEZarrOpenSciVisDatasets))
+
+- [VoDaSuRe](https://augusthoeg.github.io/VoDaSuRe/) - A large-scale dataset covering volumetric super-resolution data with micro-CT ([arXiv](https://arxiv.org/abs/2603.23153); [dataset](https://huggingface.co/datasets/AugustHoeg/VoDaSuRe))
+
+# Tools
+
+Tools that work on 3D volumetric data (like CT-scans) are sometimes developed for 3D microscopy, but natively work for visualizing other 3D data, such as tomography images:
+
+- [VolE](https://vole.allencell.org/) - Allen Institute for Cell Science's viewer for large-scale volumetric datasets, with native support for OME-Zarr.
+
+- [WebKnossos](https://webknossos.org/) - A web-based platform for visualizing, annotating, and sharing large-scale volumetric datasets.
+
+- [Neuroglancer](https://github.com/google/neuroglancer) - Google's WebGL-based viewer for volumetric data, with first class support for OME-Zarr.

resources/topic-hub/volume-em/index.md

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+(topic-volume-em)=
+
+# Volume EM
+
+Volume Electron Microscopy (vEM) includes a number of techniques for imaging large volumes of biological samples at high resolution. The OME-NGFF specification caters for this kind of big data nicely, and there are a number of resources that build upon OME-Zarr to provide additional support for vEM data.
+
+## Tools
+
+- [WebKnossos](https://webknossos.org/) - A web-based platform for visualizing, annotating, and sharing large-scale volumetric datasets. It has native support for OME-Zarr and is [widely used in the vEM community](https://home.webknossos.org/use-cases/volume-em).
+
+- [VolE](https://vole.allencell.org/) - Allen Institute for Cell Science's viewer for large-scale volumetric datasets, with native support for OME-Zarr.
+
+- [Neuroglancer](https://github.com/google/neuroglancer) - Google's WebGL-based viewer for volumetric data, with first class support for OME-Zarr.
+
+- [SyGlass](https://www.syglass.io/science) - A proprietary virtual reality platform for visualizing and analyzing large-scale volumetric datasets, with support for OME-Zarr.
+
+## Other
+
+- [WebKnossos Zarr Gallery](https://zarr.webknossos.org/)- A gallery of OME-Zarr datasets, mostly vEM, hosted by WebKnossos.
+
+- [CCP Volume EM OME-NGFF Hackathon, at EMBL-EBI, Hinxton, UK, March 2026](https://focalplane.biologists.com/2025/12/11/ccp-volume-em-ome-ngff-hackathon-2026/)
+
+- [Chapter 14 - Toward scalable reuse of vEM data: OME-Zarr to the rescue](https://www.sciencedirect.com/science/chapter/bookseries/abs/pii/S0091679X23000262) - (paywalled) book chapter describing the value of OME-Zarr for volume EM data
+
+- [Webinar for CCP volumeEM: 'OME-Zarr: A Next Generation File Format for FAIR Bioimaging Data' with Chris Barnes](https://www.ccp-volumeem.ac.uk/showandtell/may-2026)

resources/topic-hub/wsi/index.md

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+(topic-wsi)=
+
+# Whole Slide Imaging
+
+Resources related to Whole Slide Imaging (WSI) and its use in the context of the NGFF. Many of the examples come from the digital pathology community, but OME-Zarr may be used for other whole slide imaging applications.
+
+- [QuPath](https://qupath.github.io/) - Open source software for digital pathology image analysis, with support for OME-Zarr.
+
+## Lazyslide & WSIData
+
+- [wsidata: Efficient data structures and IO for whole slide image analysis](https://wsidata.readthedocs.io/en/latest/index.html)
+
+Storage backed by [SpatialData](https://spatialdata.scverse.org/), so OME-NGFF at the core.
+
+- [LazySlide: Accessible and interoperable whole slide image analysis](https://lazyslide.rtfd.io/) uses WSIData at its core.
+
+## Other tools
+
+- [fastslide](https://github.com/NKI-AI/fastslide) C++20 library for reading whole slide images, including support for OME-Zarr.
+
+- [raw2features](https://github.com/CraigMyles/raw2features) Utility for generating embeddings from whole slide images saved in OME-Zarr format.
+
+- [kfb2zarr](https://github.com/camlloyd/kfb2zarr) Rust converter for KFBio whole slide images (.kfb, .kfbf) to OME-Zarr
+
+## See also
+
+- [Bringing Open Data to Whole Slide Imaging (Besson et al, 2019.)](https://pmc.ncbi.nlm.nih.gov/articles/PMC6774793/)
+- [DICOM WSI](https://dicom.nema.org/dicom/dicomwsi/)
+- [WSI on Wikipedia](https://en.wikipedia.org/wiki/Whole_slide_imaging)