Visual analytics of time-varying multivariate ionospheric scintillation data

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dc.contributor.authorSoriano-Vargas, Aurea
dc.contributor.authorVani, Bruno C. [UNESP]
dc.contributor.authorShimabukuro, Milton H. [UNESP]
dc.contributor.authorG. Monico, João F. [UNESP]
dc.contributor.authorF. Oliveira, Maria Cristina
dc.contributor.authorHamann, Bernd
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversity of California
dc.date.accessioned2018-12-11T17:14:34Z
dc.date.available2018-12-11T17:14:34Z
dc.date.issued2017-11-01
dc.description.abstractWe present a clustering-based interactive approach to multivariate data analysis, motivated by the specific needs of scintillation data. Ionospheric scintillation is a rapid variation in the amplitude and/or phase of radio signals traveling through the ionosphere. This spatial and time-varying phenomenon is of great interest since it affects the reception quality of satellite signals. Specialized receivers at strategic regions can track multiple variables related to this phenomenon, generating a database of observations of regional ionospheric scintillation. We introduce a visual analytics solution to support analysis of such data, keeping in mind the general applicability of our approach to similar multivariate data analysis situations. Taking into account typical user questions, we combine visualization and data mining algorithms that satisfy these goals: (i) derive a representation of the variables monitored that conveys their behavior in detail, at multiple user-defined aggregation levels; (ii) provide overviews of multiple variables regarding their behavioral similarity over selected time periods; (iii) support users when identifying representative variables for characterizing scintillation behavior. We illustrate the capabilities of our proposed framework by presenting case studies driven directly by questions formulated by collaborating domain experts.en
dc.description.affiliationInstituto de Ciências Matemticas e de Computação (ICMC) University of São Paulo (USP), São Carlos, SP, 13566-590
dc.description.affiliationFaculdade de Ciências e Tecnologia (FCT) São Paulo State University (UNESP), Presidente Prudente, SP, 19060-900
dc.description.affiliationDepartment of Computer Science University of California, Davis
dc.description.affiliationUnespFaculdade de Ciências e Tecnologia (FCT) São Paulo State University (UNESP), Presidente Prudente, SP, 19060-900
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipIdFAPESP: 11/22749-8
dc.description.sponsorshipIdFAPESP: 12/24537-0
dc.description.sponsorshipIdFAPESP: 15/12831-0
dc.description.sponsorshipIdFAPESP: 17/05838
dc.description.sponsorshipIdCNPq: 305696/2013-0
dc.description.sponsorshipIdCAPES: 88881.134266/2016-01
dc.format.extent1339-1351
dc.identifierhttp://dx.doi.org/10.1016/j.cag.2017.08.013
dc.identifier.citationComputers and Graphics (Pergamon), v. 68, p. 1339-1351.
dc.identifier.doi10.1016/j.cag.2017.08.013
dc.identifier.file2-s2.0-85028943956;pdf
dc.identifier.issn0097-8493
dc.identifier.scopus2-s2.0-85028943956
dc.identifier.urihttp://hdl.handle.net/11449/175142
dc.language.isoeng
dc.relation.ispartofComputers and Graphics (Pergamon)
dc.relation.ispartofsjr0,355
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectData visualization
dc.subjectIonospheric scintillation
dc.subjectTime-varying multivariate data
dc.subjectVisual analytics
dc.subjectVisual feature selection
dc.titleVisual analytics of time-varying multivariate ionospheric scintillation dataen
dc.typeArtigo

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Artigos - Estatística - FCT