The Argo Online School: An e-learning tool to get started with Argo

The Argo Online School (AoS) is a collection of videos, animations and hands-on Python-driven Jupyter notebooks designed to make the data accessible from more than 4,000 profiling floats that constitute the Argo program. The Argo program samples, in near real-time, the upper 2,000 meters of the ocea...

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Autores: González-Santana, Alberto, Vélez-Belchí, Pedro
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/386802
Acceso en línea:http://hdl.handle.net/10261/386802
Access Level:acceso abierto
Palabra clave:Jupyter Notebooks
Oceanography
Operational oceanography
Observing systems
Robotics
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spelling The Argo Online School: An e-learning tool to get started with ArgoGonzález-Santana, AlbertoVélez-Belchí, PedroJupyter NotebooksOceanographyOperational oceanographyObserving systemsRoboticsThe Argo Online School (AoS) is a collection of videos, animations and hands-on Python-driven Jupyter notebooks designed to make the data accessible from more than 4,000 profiling floats that constitute the Argo program. The Argo program samples, in near real-time, the upper 2,000 meters of the ocean using a fleet of floats that drift with the ocean currents. The AoS consists of 28 chapters about the Argo program and its data, organized into a total of 3 lessons and 2 self-assessment sections: • Lesson 1 is intended to introduce the basics of Argo, its objectives and key elements, such as the structure of the Argo floats and their operation in the open ocean. • Lesson 2 focuses on the data coming from the Argo network, from its organization to its accessibility. Data quality control is also addressed through its two main modes: Real-Time and Delayed-Mode. • Lesson 3 is the AoS hands-on component, and it requires basic knowledge of Python. It provides a set of instructions for preparing a Python environment in case the user wants to run the Python Jupyter Notebooks on a local machine. This environment already includes recommended packages. The walk-through of Lesson 3 shows how to work with the netCDF format, how to access and process Argo data, and create visualizations to enhance understanding of the information derived from Argo data. The target audience of the AoS is high school, undergraduate or early graduate students. The programming content in Lesson 3 offers an ideal opportunity to support students pursuing a technical or science curriculum. Lessons 1 and 2 form a closed module and can be used independently by learners who wish to focus solely on Argo. It is recommended not to skip any lesson in the AoS, as the content is carefully structured from simpler to more complex concepts, providing a progressive learning experience. Users have the opportunity to self-assess their learning progress through the proposed interactive self-assessments in the AoS. The AoS has been designed to be expanded in the future to follow the implementation of new features in the Argo program.The AoS has been possible thanks to the collaboration of the Euro-Argo members, the Argo Steering Team (https://argo.ucsd.edu) and has been funded by the European Union’s Horizon 2020 research and innovation program under grant agreement Euro-Argo RISE 824131 (https://www.euro-argo.eu/EU-Projects/Euro-Argo-RISE-2019-2022). The audiovisual work has been recorded and edited by Rafael Méndez Pérez (http: //rafaelmendezp.com/) while proofreading and english coaching support was provided by Agustín Prunell-Friend. The self-assessment sections are based on John M. Shea (Smith et al., 2021) software.Peer reviewedOpen JournalsEuropean CommissionGonzález-Santana, Alberto [0000-0001-5781-9330]Vélez-Belchí, Pedro [0000-0003-2404-5679]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/386802reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/824131Vélez-Belchí, Pedro; González-Santana, Alberto; 2024; The Argo Online School: An e-learning tool to get started with Argo. En Journal of Open Source Education [Dataset] (v1.1.1); Zenodo; https://doi.org/10.5281/zenodo.13929139https://doi.org/10.21105/jose.00193Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3868022026-05-22T06:33:51Z
dc.title.none.fl_str_mv The Argo Online School: An e-learning tool to get started with Argo
title The Argo Online School: An e-learning tool to get started with Argo
spellingShingle The Argo Online School: An e-learning tool to get started with Argo
González-Santana, Alberto
Jupyter Notebooks
Oceanography
Operational oceanography
Observing systems
Robotics
title_short The Argo Online School: An e-learning tool to get started with Argo
title_full The Argo Online School: An e-learning tool to get started with Argo
title_fullStr The Argo Online School: An e-learning tool to get started with Argo
title_full_unstemmed The Argo Online School: An e-learning tool to get started with Argo
title_sort The Argo Online School: An e-learning tool to get started with Argo
dc.creator.none.fl_str_mv González-Santana, Alberto
Vélez-Belchí, Pedro
author González-Santana, Alberto
author_facet González-Santana, Alberto
Vélez-Belchí, Pedro
author_role author
author2 Vélez-Belchí, Pedro
author2_role author
dc.contributor.none.fl_str_mv European Commission
González-Santana, Alberto [0000-0001-5781-9330]
Vélez-Belchí, Pedro [0000-0003-2404-5679]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Jupyter Notebooks
Oceanography
Operational oceanography
Observing systems
Robotics
topic Jupyter Notebooks
Oceanography
Operational oceanography
Observing systems
Robotics
description The Argo Online School (AoS) is a collection of videos, animations and hands-on Python-driven Jupyter notebooks designed to make the data accessible from more than 4,000 profiling floats that constitute the Argo program. The Argo program samples, in near real-time, the upper 2,000 meters of the ocean using a fleet of floats that drift with the ocean currents. The AoS consists of 28 chapters about the Argo program and its data, organized into a total of 3 lessons and 2 self-assessment sections: • Lesson 1 is intended to introduce the basics of Argo, its objectives and key elements, such as the structure of the Argo floats and their operation in the open ocean. • Lesson 2 focuses on the data coming from the Argo network, from its organization to its accessibility. Data quality control is also addressed through its two main modes: Real-Time and Delayed-Mode. • Lesson 3 is the AoS hands-on component, and it requires basic knowledge of Python. It provides a set of instructions for preparing a Python environment in case the user wants to run the Python Jupyter Notebooks on a local machine. This environment already includes recommended packages. The walk-through of Lesson 3 shows how to work with the netCDF format, how to access and process Argo data, and create visualizations to enhance understanding of the information derived from Argo data. The target audience of the AoS is high school, undergraduate or early graduate students. The programming content in Lesson 3 offers an ideal opportunity to support students pursuing a technical or science curriculum. Lessons 1 and 2 form a closed module and can be used independently by learners who wish to focus solely on Argo. It is recommended not to skip any lesson in the AoS, as the content is carefully structured from simpler to more complex concepts, providing a progressive learning experience. Users have the opportunity to self-assess their learning progress through the proposed interactive self-assessments in the AoS. The AoS has been designed to be expanded in the future to follow the implementation of new features in the Argo program.
publishDate 2024
dc.date.none.fl_str_mv 2024
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/386802
url http://hdl.handle.net/10261/386802
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/824131
Vélez-Belchí, Pedro; González-Santana, Alberto; 2024; The Argo Online School: An e-learning tool to get started with Argo. En Journal of Open Source Education [Dataset] (v1.1.1); Zenodo; https://doi.org/10.5281/zenodo.13929139
https://doi.org/10.21105/jose.00193
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Open Journals
publisher.none.fl_str_mv Open Journals
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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