Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.0%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: RS-DAT
- License: apache-2.0
- Default Branch: main
- Homepage: https://RS-DAT.github.io/RS-DAT/
- Size: 1.26 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 6
- Releases: 0
Metadata Files
README.md
RS-DAT
The Remote Sensing Deployable Analysis environmenT (RS-DAT) is a framework for setting up an environment for exploration and analysis of remote sensing data on high-performance/high-throughput computing (HPC/HTC) systems and associated storage resources. It builds on the Pangeo ecosystem to seamlessly integrate and extend the Python and PyData ecosystem, including Dask and Xarray, and provides tools for data storage and retrieval on mass storage systems (e.g., dCache at SURF).
How can I deploy RS-DAT for my use case?
RS-DAT consists of multiple components to allow its use on different computing infrastructures, such as Snellius, Spider and Research Cloud offered by SURF, or university computing infrastructures such as DelftBlue. Please refer to the deploy documentation on how to deploy RS-DAT on various computing infrastructures.
Use cases
RS-DAT has been applied to multiple Earth Observation (EO) use cases. Feel free to explore the use cases and see if there are relevant examples for your case.
Owner
- Name: RS-DAT
- Login: RS-DAT
- Kind: organization
- Repositories: 3
- Profile: https://github.com/RS-DAT
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.0.0
title: RS-DAT
message: "If you use this software, please cite it as below."
type: software
authors:
- given-names: Francesco
family-names: Nattino
email: f.nattino@esciencecenter.nl
affiliation: Netherlands eScience Center
orcid: 'https://orcid.org/0000-0003-3286-0139'
- given-names: Meiert W.
family-names: Grootes
email: m.grootes@esciencecenter.nl
affiliation: Netherlands eScience Center
orcid: 'https://orcid.org/0000-0002-5733-4795'
- given-names: Fakhereh
family-names: Alidoost
affiliation: Netherlands eScience Center
orcid: 'https://orcid.org/0000-0001-8407-6472'
- given-names: Ou
family-names: Ku
email: o.ku@esciencecenter.nl
affiliation: Netherlands eScience Center
orcid: 'https://orcid.org/0000-0002-5373-5209'
- given-names: Pranav
family-names: Chandramouli
email: p.chandramoulI@esciencecenter.nl
affiliation: Netherlands eScience Center
orcid: 'https://orcid.org/0000-0002-7896-2969'
identifiers:
- type: doi
value: 10.5281/zenodo.7342602
description: >-
Persistent identifier for all versions of JupyterDaskonSLURM
repository-code: 'https://github.com/RS-DAT/RS-DAT'
url: 'https://rs-dat.github.io/RS-DAT/'
abstract: >-
The Remote Sensing Deployable Analysis environmenT (RS-DAT) is a framework for setting up an environment for exploration and analysis of remote sensing data on high-performance/high-throughput computing (HPC/HTC) systems and associated storage resources. It builds on the Pangeo ecosystem to seamlessly integrate and extend the Python and PyData ecosystem, including Dask and Xarray, and provides tools for data storage and retrieval on mass storage systems (e.g., dCache at SURF).
keywords:
- Dask
- Jupyter
- SLURM
- Cloud
- Docker
- Singularity
license: Apache-2.0