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bendichter
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Sep 15, 2026
rly
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Sep 16, 2026
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| We are excited to announce the release of [**HDMF-Zarr 0.14.0**](https://github.com/hdmf-dev/hdmf-zarr/releases/tag/0.14.0), a major update to the HDMF Zarr backend for storing Hierarchical Data Modeling Framework (HDMF) and Neurodata Without Borders (NWB) data using [Zarr](https://zarr.dev/). | ||
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| This release marks a major transition for HDMF-Zarr: the primary `ZarrIO` and `NWBZarrIO` classes now write and read the new **Zarr v3** format exclusively using `zarr-python` v3. HDMF-Zarr 0.14.0 also adopts the unified Zarr v3 storage convention developed in collaboration with [Zindi](https://github.com/zarr-developers/zindi) and [LINDI](https://github.com/magland/lindi), improving interoperability across tools that work with cloud-native NWB data. With the transition to Zarr v3, `ZarrDataIO` has been updated to align with the new Zarr v3 codec API, and now supports dataset sharding for improved performance on large datasets. |
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| This release marks a major transition for HDMF-Zarr: the primary `ZarrIO` and `NWBZarrIO` classes now write and read the new **Zarr v3** format exclusively using `zarr-python` v3. HDMF-Zarr 0.14.0 also adopts the unified Zarr v3 storage convention developed in collaboration with [Zindi](https://github.com/zarr-developers/zindi) and [LINDI](https://github.com/magland/lindi), improving interoperability across tools that work with cloud-native NWB data. With the transition to Zarr v3, `ZarrDataIO` has been updated to align with the new Zarr v3 codec API, and now supports dataset sharding for improved performance on large datasets. | |
| This release marks a major transition for HDMF-Zarr: the primary `ZarrIO` and `NWBZarrIO` classes now write and read the new **Zarr v3** format exclusively using `zarr-python` v3. HDMF-Zarr 0.14.0 also adopts the unified Zarr v3 storage convention developed in collaboration with [Zindi](https://github.com/bendichter/zindi) and [LINDI](https://github.com/NeurodataWithoutBorders/lindi), improving interoperability across tools that work with cloud-native NWB data. With the transition to Zarr v3, `ZarrDataIO` has been updated to align with the new Zarr v3 codec API, and now supports dataset sharding for improved performance on large datasets. |
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Looks like the linkchecker is set up to never fail because of pre-existing dead links in archived event pages. I'll make a PR to fix that.
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We should hold of merging until the hdfm-zarr 0.14 release is completed