Guided Visual Analysis of Time Series Data with Spiral Views and View Quality Measures

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dc.contributor.authorStoppacher, Stefanieen_US
dc.contributor.authorRakuschek, Julianen_US
dc.contributor.authorSchreck, Tobiasen_US
dc.contributor.editorSchulz, Hans-Jörgen_US
dc.contributor.editorVillanova, Annaen_US
dc.date.accessioned2025-05-26T06:30:28Z
dc.date.available2025-05-26T06:30:28Z
dc.date.issued2025
dc.description.abstractSeasonal variations in energy consumption and temperature, like many other time series, exhibit periodically repeating patterns. Identifying and analyzing these cyclic patterns is crucial for understanding underlying trends and predicting future behavior. Spiral visualizations are commonly used to highlight periodicity, as they intuitively arrange seasonal data in spirals. We introduce encompassing user-guided enhancements to spiral visualizations, supporting the search and analysis of patterns in cyclic time series. A key element is a parameter space visualization by an interactive heat map, which highlights important quality measures, such as similarity and monotonicity, across different segments of the spiral. This approach helps users efficiently locate areas of interest that meet specific criteria, thereby streamlining the discovery of significant patterns. To further support analysis, the system offers a linked stacked area or line chart representation of selected segments, providing a clearer understanding of the quality measures. The effectiveness of the quality measures is demonstrated by use cases on several datasets.en_US
dc.description.sectionheadersVisual Analytics Methods and Approaches
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.identifier.doi10.2312/eurova.20251097
dc.identifier.isbn978-3-03868-283-7
dc.identifier.issn2664-4487
dc.identifier.pages6 pages
dc.identifier.urihttps://doi.org/10.2312/eurova.20251097
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/eurova20251097
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing → Visual analytics
dc.subjectHuman centered computing → Visual analytics
dc.titleGuided Visual Analysis of Time Series Data with Spiral Views and View Quality Measuresen_US
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