A visualization technique to assist in the comparison of large meteorological datasets
- Autores
- Urribarri, Dana; Larrea, Martín
- Año de publicación
- 2022
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The comparison of meteorological data is a fundamental task within the techniques of meteorological forecasting due to the cyclical nature of the climate. However, interpretation of meteorological datasets can be difficult due to their large size. The goal of information visualization is to support a better understanding of the data what includes assisting the user in the data comparison process. However, few visualization techniques have been specifically developed to support the comparison process of big meteorological data. In this paper, we improved a visualization technique for large time-series comparison. The new technique is more suitable for the comparison of meteorological data.
- Materia
-
Ciencias de la Computación
Visualization
Comparison task
Comparative visualization
Meteorological data
Time series
Time misalignment - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc/4.0/
- Repositorio
.jpg)
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/11718
Ver los metadatos del registro completo
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A visualization technique to assist in the comparison of large meteorological datasetsUrribarri, DanaLarrea, MartínCiencias de la ComputaciónVisualizationComparison taskComparative visualizationMeteorological dataTime seriesTime misalignmentThe comparison of meteorological data is a fundamental task within the techniques of meteorological forecasting due to the cyclical nature of the climate. However, interpretation of meteorological datasets can be difficult due to their large size. The goal of information visualization is to support a better understanding of the data what includes assisting the user in the data comparison process. However, few visualization techniques have been specifically developed to support the comparison process of big meteorological data. In this paper, we improved a visualization technique for large time-series comparison. The new technique is more suitable for the comparison of meteorological data.2022-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/11718enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cag.2022.02.011info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:00Zoai:digital.cic.gba.gob.ar:11746/11718Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:00.572CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
| dc.title.none.fl_str_mv |
A visualization technique to assist in the comparison of large meteorological datasets |
| title |
A visualization technique to assist in the comparison of large meteorological datasets |
| spellingShingle |
A visualization technique to assist in the comparison of large meteorological datasets Urribarri, Dana Ciencias de la Computación Visualization Comparison task Comparative visualization Meteorological data Time series Time misalignment |
| title_short |
A visualization technique to assist in the comparison of large meteorological datasets |
| title_full |
A visualization technique to assist in the comparison of large meteorological datasets |
| title_fullStr |
A visualization technique to assist in the comparison of large meteorological datasets |
| title_full_unstemmed |
A visualization technique to assist in the comparison of large meteorological datasets |
| title_sort |
A visualization technique to assist in the comparison of large meteorological datasets |
| dc.creator.none.fl_str_mv |
Urribarri, Dana Larrea, Martín |
| author |
Urribarri, Dana |
| author_facet |
Urribarri, Dana Larrea, Martín |
| author_role |
author |
| author2 |
Larrea, Martín |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias de la Computación Visualization Comparison task Comparative visualization Meteorological data Time series Time misalignment |
| topic |
Ciencias de la Computación Visualization Comparison task Comparative visualization Meteorological data Time series Time misalignment |
| dc.description.none.fl_txt_mv |
The comparison of meteorological data is a fundamental task within the techniques of meteorological forecasting due to the cyclical nature of the climate. However, interpretation of meteorological datasets can be difficult due to their large size. The goal of information visualization is to support a better understanding of the data what includes assisting the user in the data comparison process. However, few visualization techniques have been specifically developed to support the comparison process of big meteorological data. In this paper, we improved a visualization technique for large time-series comparison. The new technique is more suitable for the comparison of meteorological data. |
| description |
The comparison of meteorological data is a fundamental task within the techniques of meteorological forecasting due to the cyclical nature of the climate. However, interpretation of meteorological datasets can be difficult due to their large size. The goal of information visualization is to support a better understanding of the data what includes assisting the user in the data comparison process. However, few visualization techniques have been specifically developed to support the comparison process of big meteorological data. In this paper, we improved a visualization technique for large time-series comparison. The new technique is more suitable for the comparison of meteorological data. |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022-05 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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https://digital.cic.gba.gob.ar/handle/11746/11718 |
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https://digital.cic.gba.gob.ar/handle/11746/11718 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cag.2022.02.011 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc/4.0/ |
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openAccess |
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application/pdf |
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