TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data

Aurea Soriano-Vargas, Bernd Hamann, Maria Cristina F de Oliveira

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

6 Citas (Scopus)

Resumen

We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights. We consolidated the considered analysis and visualization methods in one framework, called TV-MV Analytics. TV-MV Analytics effectively combines visualization and data mining algorithms providing the following capabilities: (1) visual exploration of multivariate data at different temporal scales, and (2) a hierarchical small multiples visualization combined with interactive clustering and multidimensional projection to detect temporal relationships in the data. We demonstrate the value of our framework for specific scenarios, by studying three use cases that were validated and discussed with domain experts.

Idioma originalInglés
Páginas (desde-hasta)3-23
Número de páginas21
PublicaciónInformation Visualization
Volumen19
N.º1
DOI
EstadoPublicada - 1 ene. 2020
Publicado de forma externa

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