iStar (i*): An interactive star coordinates approach for high-dimensional data exploration

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We would like to thank the financial support from the National Council for Science, Technology and Technological Innovation - CONCYTEC, Peru (grant FONDECYT 011-2013 Master Program), the São Paulo Research Foundation - FAPESP (grants #2013/00191-0 and #2011/22749-8) and the National Counsel of Techn...

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Detalles Bibliográficos
Autores: Garcia Zanabria G., Nonato L.G., Gomez-Nieto E.
Formato: artículo
Fecha de Publicación:2016
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/669
Enlace del recurso:https://hdl.handle.net/20.500.12390/669
https://doi.org/10.1016/j.cag.2016.08.007
Nivel de acceso:acceso abierto
Materia:Visualization method
Clustering algorithms
Flow visualization
Visualization
Attribute importance
Clustering mechanism
Experiments and case studies
Feasible alternatives
High dimensional data
Multidimensional data
Star coordinates
Data visualization
https://purl.org/pe-repo/ocde/ford#2.02.04
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oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/669
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
title iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
spellingShingle iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
Garcia Zanabria G.
Visualization method
Clustering algorithms
Flow visualization
Visualization
Visualization
Attribute importance
Clustering mechanism
Experiments and case studies
Feasible alternatives
High dimensional data
Multidimensional data
Star coordinates
Data visualization
https://purl.org/pe-repo/ocde/ford#2.02.04
title_short iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
title_full iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
title_fullStr iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
title_full_unstemmed iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
title_sort iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
author Garcia Zanabria G.
author_facet Garcia Zanabria G.
Nonato L.G.
Gomez-Nieto E.
author_role author
author2 Nonato L.G.
Gomez-Nieto E.
author2_role author
author
dc.contributor.author.fl_str_mv Garcia Zanabria G.
Nonato L.G.
Gomez-Nieto E.
dc.subject.none.fl_str_mv Visualization method
topic Visualization method
Clustering algorithms
Flow visualization
Visualization
Visualization
Attribute importance
Clustering mechanism
Experiments and case studies
Feasible alternatives
High dimensional data
Multidimensional data
Star coordinates
Data visualization
https://purl.org/pe-repo/ocde/ford#2.02.04
dc.subject.es_PE.fl_str_mv Clustering algorithms
Flow visualization
Visualization
Visualization
Attribute importance
Clustering mechanism
Experiments and case studies
Feasible alternatives
High dimensional data
Multidimensional data
Star coordinates
Data visualization
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.04
description We would like to thank the financial support from the National Council for Science, Technology and Technological Innovation - CONCYTEC, Peru (grant FONDECYT 011-2013 Master Program), the São Paulo Research Foundation - FAPESP (grants #2013/00191-0 and #2011/22749-8) and the National Counsel of Technological and Scientific Development - CNPq, Brazil (grant #302643/2013-3).
publishDate 2016
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/669
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.cag.2016.08.007
dc.identifier.scopus.none.fl_str_mv 2-s2.0-84992412635
url https://hdl.handle.net/20.500.12390/669
https://doi.org/10.1016/j.cag.2016.08.007
identifier_str_mv 2-s2.0-84992412635
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Computers and Graphics (Pergamon)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier Ltd
publisher.none.fl_str_mv Elsevier Ltd
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
_version_ 1844883090465357824
spelling Publicationrp01507600rp01508600rp01234500Garcia Zanabria G.Nonato L.G.Gomez-Nieto E.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2016https://hdl.handle.net/20.500.12390/669https://doi.org/10.1016/j.cag.2016.08.0072-s2.0-84992412635We would like to thank the financial support from the National Council for Science, Technology and Technological Innovation - CONCYTEC, Peru (grant FONDECYT 011-2013 Master Program), the São Paulo Research Foundation - FAPESP (grants #2013/00191-0 and #2011/22749-8) and the National Counsel of Technological and Scientific Development - CNPq, Brazil (grant #302643/2013-3).Star Coordinates is an important visualization method able to reveal patterns and groups from multidimensional data while still showing the impact of data attributes in the formation of such patterns and groups. Despite its usefulness, Star Coordinates bears limitations that impair its use in several scenarios. For instance, when the number of data dimensions is high, the resulting visualization becomes cluttered, hampering the joint analysis of attribute importance and group/pattern formation. In this paper, we propose a novel method that renders Star Coordinates a feasible alternative to analyze high-dimensional data. The proposed method relies on a clustering mechanism to group attributes in order to mitigate visual clutter. Clustering can be performed automatically as well as interactively, allowing the analysis of how particular groups of attributes impact on the radial layout, thus assisting users in the understanding of data. The effectiveness of our approach is shown through a set of experiments and case studies, which attest its usefulness in practical applications.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengElsevier LtdComputers and Graphics (Pergamon)info:eu-repo/semantics/openAccessVisualization methodClustering algorithms-1Flow visualization-1Visualization-1Visualization-1Attribute importance-1Clustering mechanism-1Experiments and case studies-1Feasible alternatives-1High dimensional data-1Multidimensional data-1Star coordinates-1Data visualization-1https://purl.org/pe-repo/ocde/ford#2.02.04-1iStar (i*): An interactive star coordinates approach for high-dimensional data explorationinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#20.500.12390/669oai:repositorio.concytec.gob.pe:20.500.12390/6692024-05-30 15:35:57.758http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="49bd2faf-d3b7-4091-a48b-ce66d369f5b2"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>iStar (i*): An interactive star coordinates approach for high-dimensional data exploration</Title> <PublishedIn> <Publication> <Title>Computers and Graphics (Pergamon)</Title> </Publication> </PublishedIn> <PublicationDate>2016</PublicationDate> <DOI>https://doi.org/10.1016/j.cag.2016.08.007</DOI> <SCP-Number>2-s2.0-84992412635</SCP-Number> <Authors> <Author> <DisplayName>Garcia Zanabria G.</DisplayName> <Person id="rp01507" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Nonato L.G.</DisplayName> <Person id="rp01508" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Gomez-Nieto E.</DisplayName> <Person id="rp01234" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Elsevier Ltd</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Visualization method</Keyword> <Keyword>Clustering algorithms</Keyword> <Keyword>Flow visualization</Keyword> <Keyword>Visualization</Keyword> <Keyword>Visualization</Keyword> <Keyword>Attribute importance</Keyword> <Keyword>Clustering mechanism</Keyword> <Keyword>Experiments and case studies</Keyword> <Keyword>Feasible alternatives</Keyword> <Keyword>High dimensional data</Keyword> <Keyword>Multidimensional data</Keyword> <Keyword>Star coordinates</Keyword> <Keyword>Data visualization</Keyword> <Abstract>Star Coordinates is an important visualization method able to reveal patterns and groups from multidimensional data while still showing the impact of data attributes in the formation of such patterns and groups. Despite its usefulness, Star Coordinates bears limitations that impair its use in several scenarios. For instance, when the number of data dimensions is high, the resulting visualization becomes cluttered, hampering the joint analysis of attribute importance and group/pattern formation. In this paper, we propose a novel method that renders Star Coordinates a feasible alternative to analyze high-dimensional data. The proposed method relies on a clustering mechanism to group attributes in order to mitigate visual clutter. Clustering can be performed automatically as well as interactively, allowing the analysis of how particular groups of attributes impact on the radial layout, thus assisting users in the understanding of data. The effectiveness of our approach is shown through a set of experiments and case studies, which attest its usefulness in practical applications.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
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iStar (i*): An interactive star coordinates approach for high-dimensional data exploration
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