Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.ecoinf.2018.05.003 http://hdl.handle.net/11449/179909 |
Resumo: | Phenology is a traditional science that investigates the periodic phenomena of plants and animals and their relations to environmental conditions. Typically plant phenological studies are based on observations made by phenology experts in the field over time and the correlation with climate data collected by weather sensors. Although within the visualization community several approaches have been proposed for visualizing data that vary over time, many of them have a specific purpose and cannot be applied to phenology studies. Besides that, phenology experts increasingly need tools for managing appropriately long-term time series with many variables of different data types, as well as to identify cyclical temporal patterns. In this work, we propose a novel approach to visualize phenological data by combining radial visual structures along with visual rhythms. Radial visual structures are used to provide contextual insights regarding cyclical phenomena, while the visual rhythm encoding is used to summarize long-term time series into compact representations. We developed, evaluate, and validate our proposal with phenology experts using plant phenology direct observational data both at individuals and species levels. |
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Repositório Institucional da UNESP |
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Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysisMultivariate time seriesPhenology visualizationRadial visualizationVisual rhythmPhenology is a traditional science that investigates the periodic phenomena of plants and animals and their relations to environmental conditions. Typically plant phenological studies are based on observations made by phenology experts in the field over time and the correlation with climate data collected by weather sensors. Although within the visualization community several approaches have been proposed for visualizing data that vary over time, many of them have a specific purpose and cannot be applied to phenology studies. Besides that, phenology experts increasingly need tools for managing appropriately long-term time series with many variables of different data types, as well as to identify cyclical temporal patterns. In this work, we propose a novel approach to visualize phenological data by combining radial visual structures along with visual rhythms. Radial visual structures are used to provide contextual insights regarding cyclical phenomena, while the visual rhythm encoding is used to summarize long-term time series into compact representations. We developed, evaluate, and validate our proposal with phenology experts using plant phenology direct observational data both at individuals and species levels.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Institute of Computing University of Campinas (UNICAMP)UNESP - São Paulo State University Institute of Biosciences Department of Botany Phenology LaboratoryUNESP - São Paulo State University Institute of Biosciences Department of Botany Phenology LaboratoryFAPESP: 2007/59779-6FAPESP: 2009/18438-7FAPESP: 2010/51307-0FAPESP: 2013/50155-0FAPESP: 2013/50169-1FAPESP: 2014/12236-1FAPESP: 2014/50715-9FAPESP: 2015/24494-8FAPESP: 2016/50250-1FAPESP: 2017/20945-0Universidade Estadual de Campinas (UNICAMP)Universidade Estadual Paulista (Unesp)Mariano, Greice C.Staggemeier, Vanessa G. [UNESP]Morellato, Leonor Patricia Cerdeira [UNESP]Torres, Ricardo da S.2018-12-11T17:37:15Z2018-12-11T17:37:15Z2018-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article19-35application/pdfhttp://dx.doi.org/10.1016/j.ecoinf.2018.05.003Ecological Informatics, v. 46, p. 19-35.1574-9541http://hdl.handle.net/11449/17990910.1016/j.ecoinf.2018.05.0032-s2.0-850478317122-s2.0-85047831712.pdf1012217731137451Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEcological Informatics0,778info:eu-repo/semantics/openAccess2023-12-23T06:22:51Zoai:repositorio.unesp.br:11449/179909Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:07:16.168225Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
title |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
spellingShingle |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis Mariano, Greice C. Multivariate time series Phenology visualization Radial visualization Visual rhythm |
title_short |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
title_full |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
title_fullStr |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
title_full_unstemmed |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
title_sort |
Multivariate cyclical data visualization using radial visual rhythms: A case study in phenology analysis |
author |
Mariano, Greice C. |
author_facet |
Mariano, Greice C. Staggemeier, Vanessa G. [UNESP] Morellato, Leonor Patricia Cerdeira [UNESP] Torres, Ricardo da S. |
author_role |
author |
author2 |
Staggemeier, Vanessa G. [UNESP] Morellato, Leonor Patricia Cerdeira [UNESP] Torres, Ricardo da S. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual de Campinas (UNICAMP) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Mariano, Greice C. Staggemeier, Vanessa G. [UNESP] Morellato, Leonor Patricia Cerdeira [UNESP] Torres, Ricardo da S. |
dc.subject.por.fl_str_mv |
Multivariate time series Phenology visualization Radial visualization Visual rhythm |
topic |
Multivariate time series Phenology visualization Radial visualization Visual rhythm |
description |
Phenology is a traditional science that investigates the periodic phenomena of plants and animals and their relations to environmental conditions. Typically plant phenological studies are based on observations made by phenology experts in the field over time and the correlation with climate data collected by weather sensors. Although within the visualization community several approaches have been proposed for visualizing data that vary over time, many of them have a specific purpose and cannot be applied to phenology studies. Besides that, phenology experts increasingly need tools for managing appropriately long-term time series with many variables of different data types, as well as to identify cyclical temporal patterns. In this work, we propose a novel approach to visualize phenological data by combining radial visual structures along with visual rhythms. Radial visual structures are used to provide contextual insights regarding cyclical phenomena, while the visual rhythm encoding is used to summarize long-term time series into compact representations. We developed, evaluate, and validate our proposal with phenology experts using plant phenology direct observational data both at individuals and species levels. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-11T17:37:15Z 2018-12-11T17:37:15Z 2018-07-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.ecoinf.2018.05.003 Ecological Informatics, v. 46, p. 19-35. 1574-9541 http://hdl.handle.net/11449/179909 10.1016/j.ecoinf.2018.05.003 2-s2.0-85047831712 2-s2.0-85047831712.pdf 1012217731137451 |
url |
http://dx.doi.org/10.1016/j.ecoinf.2018.05.003 http://hdl.handle.net/11449/179909 |
identifier_str_mv |
Ecological Informatics, v. 46, p. 19-35. 1574-9541 10.1016/j.ecoinf.2018.05.003 2-s2.0-85047831712 2-s2.0-85047831712.pdf 1012217731137451 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ecological Informatics 0,778 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
19-35 application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129286894256128 |