Democratizing Argentine Marine Science Data Through Linked Open Data

Autores
Zárate, Marcos Daniel; Buckle, Carlos; Lewis, Mirtha Noemí; Delrieux, Claudio; Ceballos, Dario; Nuñez, Gustavo
Año de publicación
2022
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper we expose experiences carried out during the last five years in the domain of Argentine marine sciences. Specifically data generated by Pampa Azul Argentine initiative to improve the publication of data using the advantages provided by Linked Open Data (LOD), Knowledge Graph (KG) and FAIR principles. The focus is on: a) to provide a conceptual analysis of traditional data publication in marine science, b) to describe projects based on LOD that involve information from Argentina, we mainly focus on the OceanGraph KG project, c) generate recommendations for data management for its best use in marine science.
XIX Workshop Base de Datos y Minería de Datos (WBDMD)
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Linked Open Data
FAIR
Pampa Azul
Knowledge Graph
Marine Science
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/149638

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spelling Democratizing Argentine Marine Science Data Through Linked Open DataZárate, Marcos DanielBuckle, CarlosLewis, Mirtha NoemíDelrieux, ClaudioCeballos, DarioNuñez, GustavoCiencias InformáticasLinked Open DataFAIRPampa AzulKnowledge GraphMarine ScienceIn this paper we expose experiences carried out during the last five years in the domain of Argentine marine sciences. Specifically data generated by Pampa Azul Argentine initiative to improve the publication of data using the advantages provided by Linked Open Data (LOD), Knowledge Graph (KG) and FAIR principles. The focus is on: a) to provide a conceptual analysis of traditional data publication in marine science, b) to describe projects based on LOD that involve information from Argentina, we mainly focus on the OceanGraph KG project, c) generate recommendations for data management for its best use in marine science.XIX Workshop Base de Datos y Minería de Datos (WBDMD)Red de Universidades con Carreras en Informática2022-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/149638enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-1364-31-2info:eu-repo/semantics/reference/hdl/10915/149102info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:38:22Zoai:sedici.unlp.edu.ar:10915/149638Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:38:23.116SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Democratizing Argentine Marine Science Data Through Linked Open Data
title Democratizing Argentine Marine Science Data Through Linked Open Data
spellingShingle Democratizing Argentine Marine Science Data Through Linked Open Data
Zárate, Marcos Daniel
Ciencias Informáticas
Linked Open Data
FAIR
Pampa Azul
Knowledge Graph
Marine Science
title_short Democratizing Argentine Marine Science Data Through Linked Open Data
title_full Democratizing Argentine Marine Science Data Through Linked Open Data
title_fullStr Democratizing Argentine Marine Science Data Through Linked Open Data
title_full_unstemmed Democratizing Argentine Marine Science Data Through Linked Open Data
title_sort Democratizing Argentine Marine Science Data Through Linked Open Data
dc.creator.none.fl_str_mv Zárate, Marcos Daniel
Buckle, Carlos
Lewis, Mirtha Noemí
Delrieux, Claudio
Ceballos, Dario
Nuñez, Gustavo
author Zárate, Marcos Daniel
author_facet Zárate, Marcos Daniel
Buckle, Carlos
Lewis, Mirtha Noemí
Delrieux, Claudio
Ceballos, Dario
Nuñez, Gustavo
author_role author
author2 Buckle, Carlos
Lewis, Mirtha Noemí
Delrieux, Claudio
Ceballos, Dario
Nuñez, Gustavo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Linked Open Data
FAIR
Pampa Azul
Knowledge Graph
Marine Science
topic Ciencias Informáticas
Linked Open Data
FAIR
Pampa Azul
Knowledge Graph
Marine Science
dc.description.none.fl_txt_mv In this paper we expose experiences carried out during the last five years in the domain of Argentine marine sciences. Specifically data generated by Pampa Azul Argentine initiative to improve the publication of data using the advantages provided by Linked Open Data (LOD), Knowledge Graph (KG) and FAIR principles. The focus is on: a) to provide a conceptual analysis of traditional data publication in marine science, b) to describe projects based on LOD that involve information from Argentina, we mainly focus on the OceanGraph KG project, c) generate recommendations for data management for its best use in marine science.
XIX Workshop Base de Datos y Minería de Datos (WBDMD)
Red de Universidades con Carreras en Informática
description In this paper we expose experiences carried out during the last five years in the domain of Argentine marine sciences. Specifically data generated by Pampa Azul Argentine initiative to improve the publication of data using the advantages provided by Linked Open Data (LOD), Knowledge Graph (KG) and FAIR principles. The focus is on: a) to provide a conceptual analysis of traditional data publication in marine science, b) to describe projects based on LOD that involve information from Argentina, we mainly focus on the OceanGraph KG project, c) generate recommendations for data management for its best use in marine science.
publishDate 2022
dc.date.none.fl_str_mv 2022-10
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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