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2color merged 2 commits into from
Feb 27, 2026
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Add link to ORCESTRA case study in menu #2261

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12f2cdb
Add link to ORCESTRA case study in menu
2color Feb 27, 2026
e4b1d80
Fix links
2color Feb 27, 2026
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1 change: 1 addition & 0 deletions docs/.vuepress/config.js
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Expand Up @@ -92,6 +92,7 @@ module.exports = {
{text: 'Fleek', link : '/case-studies/fleek'},
{text: 'LikeCoin', link : '/case-studies/likecoin'},
{text: 'Morpheus.Network', link : '/case-studies/morpheus'},
{text: 'ORCESTRA', link : '/case-studies/orcestra'},
{text: 'Snapshot',link : '/case-studies/snapshot'},
]
}
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8 changes: 4 additions & 4 deletions docs/how-to/scientific-data/landscape-guide.md
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Expand Up @@ -130,10 +130,10 @@ Zarr has seen widespread adoption across scientific domains, for example:
- Optimising Zarr chunk size is a nuanced topic and largely dependent on the access patterns of data
- The established convention is to try to align Zarr chunk sizes with the IPFS maximal chunk size of 1 MiB whenever possible so that each Zarr chunk fetched maps to a single IPFS block.
- There are many resources that cover this in more details:
- https://zarr.readthedocs.io/en/stable/user-guide/performance/
- https://element84.com/software-engineering/chunks-and-chunkability-tyranny-of-the-chunk/
- https://eopf-toolkit.github.io/eopf-101/03_about_chunking/31_zarr_chunking_intro.html
- https://esipfed.github.io/cloud-computing-cluster/optimization-practices.html
- [https://zarr.readthedocs.io/en/stable/user-guide/performance/](https://zarr.readthedocs.io/en/stable/user-guide/performance/)
- [https://element84.com/software-engineering/chunks-and-chunkability-tyranny-of-the-chunk/](https://element84.com/software-engineering/chunks-and-chunkability-tyranny-of-the-chunk/)
- [https://eopf-toolkit.github.io/eopf-101/03_about_chunking/31_zarr_chunking_intro.html](https://eopf-toolkit.github.io/eopf-101/03_about_chunking/31_zarr_chunking_intro.html)
- [https://esipfed.github.io/cloud-computing-cluster/optimization-practices.html](https://esipfed.github.io/cloud-computing-cluster/optimization-practices.html)
- There are a number of trade-offs to consider with UnixFS:
- Overhead of around 0.5%-1% for the additional metadata and proto
- But you might want to keep original copy of the data before encoding with UnixFS so that might double it
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