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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

P. Federico, S. Hoffmann, A. Rind, W. Aigner, S. Miksch:
"Qualizon Graphs: Space-Efficient Time-Series Visualization with Qualitative Abstractions";
Vortrag: 12th International Working Conference on Advanced Visual Interfaces (AVI2014), Como (Italy); 27.05.2014 - 30.05.2014; in: "Proceedings of the Working Conference on Advanced Visual Interfaces (AVI2014)", ACM, (2014), ISBN: 978-1-4503-2775-6; S. 273 - 280.



Kurzfassung englisch:
In several application fields, the joint visualization of quantitative data and qualitative abstractions can help analysts make sense of complex time series data by associating precise numeric values with corresponding domain-specific interpretations, such as good, bad, high, low, normal. At the same time, the need to analyse large multivariate time-oriented datasets often calls for keeping visualizations as compact as possible. In this paper, we introduce Qualizon Graphs, a compact visualization that combines quantitative data and qualitative abstractions. It is based on the well known Horizon Graphs, but instead of a predefined number of equally sized bands, it uses as many bands as qualitative categories with corresponding different sizes. In this way, Qualizon Graphs increase the data density of visualized quantitative values and inherently integrate qualitative abstractions. A user study shows that Qualizon Graphs are as fast and accurate as Horizon Graphs for quantitative data, and are an alternative to state-of-the-art visualizations for both quantitative and qualitative data, enabling a trade-off between speed and accuracy.

Schlagworte:
Information Visualization, Time Series Data, Qualitative Abstractions, Temporal Abstractions, Horizon Graphs


"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1145/2598153.2598172

Elektronische Version der Publikation:
http://publik.tuwien.ac.at/files/PubDat_228036.pdf



Zugeordnete Projekte:
Projektleitung Silvia Miksch:
CVAST: Centre for Visual Analytics Science and Technology (Laura Bassi Centre of Expertise)

Projektleitung Silvia Miksch:
MobiGuide: Führen von PatientInnen immer & überall