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

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)3-23
Number of pages21
JournalInformation Visualization
Volume19
Issue number1
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes

Keywords

  • Visual analytics
  • data analytics
  • data visualization
  • time-varying multivariate data
  • visual feature selection

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