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Aesthetics and Ordering in Stacked Area Charts

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DOI

Stacked area charts are a common visualisation type for sets of time series. Yet, they are also known to be challenging to read, in particular if the time series exhibit much fluctuation or even abrupt changes. In this paper, we introduce a novel approach to improving the layout of stacked area charts by means of reordering the time series in the stack. This approach breaks down into two parts: First, we gather aesthetic criteria and define associated quality metrics for stacked area charts. Second, we use these quality metrics together with a new algorithm called UpwardsOpt to find orderings of the stacked time series that optimise a chart's aesthetic properties. The produced orderings guarantee optimality in the sense that no better result can be obtained by moving any individual time series to a different position in the stack. In use cases, we illustrate how the flexibility provided by the introduced aesthetic criteria can make data properties better visible, as well as how our ordering algorithm is able to yield better orderings than the state-of-the-art approach. An open source implementation of our algorithm is provided to facilitate its reuse and the reproducibility of our results.
OriginalsprogEngelsk
TitelDiagrammatic representation and inference : 12th International Conference on the Theory and Application of Diagrams (DIAGRAMS'21)
RedaktørerAmrita Basu, Gem Stapleton, Sven Linker, Catherine Legg, Emmanuel Manalo, Petrucio Viana
Antal sider17
UdgivelsesstedCham
ForlagSpringer
Udgivelsesår2021
Sider3-19
ISBN (trykt)978-3-030-86061-5
ISBN (Elektronisk)978-3-030-86062-2
DOI
StatusUdgivet - 2021
Begivenhed12th International Conference on the Theory and Application of Diagrams: Diagrams 2021 - Virtual
Varighed: 28 sep. 202130 sep. 2021
Konferencens nummer: 12

Konference

Konference12th International Conference on the Theory and Application of Diagrams
Nummer12
LokationVirtual
Periode28/09/202130/09/2021
SerietitelLecture Notes in Computer Science
Vol/bind12909
ISSN0302-9743

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