Getting Started

Installation

We recommend installing the latest release of OceanDataStore into a dedicated Python virtual environment.

pip (latest release)pip (latest commits)

pip install oceandatastore

pip install git+https://github.com/NOC-MSM/OceanDataStore.git

Setting up a virtual environment

Using venv:

python3 -m venv env_ods
source env_ods/bin/activate

Using conda / miniconda / mamba:

conda create -n env_ods python=3.13
conda activate env_ods

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Usage

Publish Data — CLI

Write and update data to S3-compatible object stores (e.g. JASMIN Object Store):

Command	Description
send_to_zarr	Send local NetCDF file(s) to a new Zarr store
update_zarr	Append local NetCDF file(s) to an existing Zarr store
send_to_icechunk	Send local NetCDF file(s) to a new Icechunk repository
update_icechunk	Append local NetCDF file(s) to an existing Icechunk repository
list	List objects in a cloud object store bucket

→ Publish User Guide · How-To Guide · Examples

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Analyse — OceanDataCatalog

Search and access ARCO ocean datacubes as familar xarray Datasets or Icechunk repositories:

• Discover ocean model and observational data via a STAC catalog.
• Filter by collection, variable name, or data type.
• Subset data by spatial bounding box and/or time range.

→ Analyse User Guide · How-To Guide · Browse Catalog

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Next Steps...

I want to…	Go to…
Publish ocean model outputs	Publish → User Guide
Publish large simulations in parallel	Publish → How-To Guide
Browse publicly available ocean data	Explore → Dataset Catalog
Discover ocean data by variable	Analyse → User Guide
Access ocean data stored in the cloud using Python	Analyse → How-To Guide
Explore end-to-end examples	Publish Examples · Analyse Examples