Aigner, W., Miksch, S., Schumann, H., & Tominski, C. (2023). Visualization of Time-Oriented Data (2.). Springer London. https://doi.org/10.1007/978-1-4471-7527-8
Time is an exceptional dimension with high relevance in medicine, engineering, business, science, biography, history, planning, or project management. Understanding time-oriented data via visual representations enables us to learn from the past in order to predict, plan, and build the future.
This second edition builds upon the great success of the first edition. It maintains a brief introduction to visualization and a review of historical time-oriented visual representations. At its core, the book develops a systematic view of the visualization of time-oriented data. Separate chapters discuss interaction techniques and computational methods for supporting the visual data analysis. Many examples and figures illustrate the introduced concepts and techniques.
So, what is new for the second edition? First of all, the second edition is now published as an open-access book so that anyone interested in the visualization of time and time-oriented data can read it. Second, the entire content has been revised and expanded to represent state-of-the-art knowledge. The chapter on interaction support now includes advanced methods for interacting with visual representations of time-oriented data. The second edition also covers the topics of data quality as well as segmentation and labeling. The comprehensive survey of classic and contemporary visualization techniques now provides more than 150 self-contained descriptions accompanied by illustrations and corresponding references. A completely new chapter describes how the structured survey can be used for the guided selection of suitable visualization techniques.
For the second edition, our TimeViz Browser, the digital pendant to the survey of visualization techniques, received a major upgrade. It includes the same set of techniques as the book, but comes with additional filter and search facilities allowing scientists and practitioners to find exactly the solutions they are interested in.
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Project title:
Wissensunterstützte Visual Analytics: P 31419-N31 (FWF - Österr. Wissenschaftsfonds) Blind Source Separation in Time and Space: P 31881-N32 (FWF - Österr. Wissenschaftsfonds) ArtVis: Dynamische Netzwerk für die digitale Kunstgeschichte: P35767-N (FWF - Österr. Wissenschaftsfonds) Guidance-Enriched Visual Analytics for Temporal Data: ICT19-47 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds) Domain-adaptive Remote sensing Image Analysis with Human-in-the-loop: 880883 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) Visuelle Analytik und Computer Vision treffen auf kulturelles Erbe: DFH 37-N (FWF - Österr. Wissenschaftsfonds)
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Research Areas:
Visual Computing and Human-Centered Technology: 100%