A review on dynamic time warping in data visualization

Autores
Urribarri, Dana K.
Año de publicación
2025
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Dynamic Time Warping (DTW) is an algorithm for measuring the similarity between two time series that may vary in speed or length. Its ability to align sequences non-linearly makes it appropriate in a wide range of domains. However, its quadratic complexity and inability to handle data streams have been an obstacle to its adoption in modern data visualization. This paper explores the expansive scope of DTW within data visualization, focusing on its application in time series comparison. It introduces the fundamentals of DTW, explores the vast variety of modifications, and analyzes existing visualization techniques that uses DTW. Furthermore, since standard DTW is inadequate for modern visualization challenges (big data, streaming data, multidimensional data), it highlights the critical relevance of advanced DTW variants.
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Algorithm
DTW
Data visualization
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:10915/191271
Acceder
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network_name_str SEDICI (UNLP)
spelling A review on dynamic time warping in data visualizationUrribarri, Dana K.Ciencias InformáticasAlgorithmDTWData visualizationDynamic Time Warping (DTW) is an algorithm for measuring the similarity between two time series that may vary in speed or length. Its ability to align sequences non-linearly makes it appropriate in a wide range of domains. However, its quadratic complexity and inability to handle data streams have been an obstacle to its adoption in modern data visualization. This paper explores the expansive scope of DTW within data visualization, focusing on its application in time series comparison. It introduces the fundamentals of DTW, explores the vast variety of modifications, and analyzes existing visualization techniques that uses DTW. Furthermore, since standard DTW is inadequate for modern visualization challenges (big data, streaming data, multidimensional data), it highlights the critical relevance of advanced DTW variants.Red de Universidades con Carreras en Informática2025-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf385-394http://sedici.unlp.edu.ar/handle/10915/191271enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-8258-99-7info:eu-repo/semantics/reference/hdl/10915/189846info: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:UNLP2026-03-26T09:21:32Zoai:sedici.unlp.edu.ar:10915/191271Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-03-26 09:21:33.146SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A review on dynamic time warping in data visualization
title A review on dynamic time warping in data visualization
spellingShingle A review on dynamic time warping in data visualization
Urribarri, Dana K.
Ciencias Informáticas
Algorithm
DTW
Data visualization
title_short A review on dynamic time warping in data visualization
title_full A review on dynamic time warping in data visualization
title_fullStr A review on dynamic time warping in data visualization
title_full_unstemmed A review on dynamic time warping in data visualization
title_sort A review on dynamic time warping in data visualization
dc.creator.none.fl_str_mv Urribarri, Dana K.
author Urribarri, Dana K.
author_facet Urribarri, Dana K.
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Algorithm
DTW
Data visualization
topic Ciencias Informáticas
Algorithm
DTW
Data visualization
dc.description.none.fl_txt_mv Dynamic Time Warping (DTW) is an algorithm for measuring the similarity between two time series that may vary in speed or length. Its ability to align sequences non-linearly makes it appropriate in a wide range of domains. However, its quadratic complexity and inability to handle data streams have been an obstacle to its adoption in modern data visualization. This paper explores the expansive scope of DTW within data visualization, focusing on its application in time series comparison. It introduces the fundamentals of DTW, explores the vast variety of modifications, and analyzes existing visualization techniques that uses DTW. Furthermore, since standard DTW is inadequate for modern visualization challenges (big data, streaming data, multidimensional data), it highlights the critical relevance of advanced DTW variants.
Red de Universidades con Carreras en Informática
description Dynamic Time Warping (DTW) is an algorithm for measuring the similarity between two time series that may vary in speed or length. Its ability to align sequences non-linearly makes it appropriate in a wide range of domains. However, its quadratic complexity and inability to handle data streams have been an obstacle to its adoption in modern data visualization. This paper explores the expansive scope of DTW within data visualization, focusing on its application in time series comparison. It introduces the fundamentals of DTW, explores the vast variety of modifications, and analyzes existing visualization techniques that uses DTW. Furthermore, since standard DTW is inadequate for modern visualization challenges (big data, streaming data, multidimensional data), it highlights the critical relevance of advanced DTW variants.
publishDate 2025
dc.date.none.fl_str_mv 2025-10
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info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/191271
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-8258-99-7
info:eu-repo/semantics/reference/hdl/10915/189846
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
385-394
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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