Interactive Visual Data Analysis

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Interactive Visual Data Analysis

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內容描述

In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data.
The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today's large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis.
The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains.
Features:

Dedicated to the synthesis of visual, interactive, and analysis methods
Systematic top-down view on visualization, interaction, and automatic analysis
Broad coverage of fundamental and advanced visualization techniques
Comprehensive chapter on interacting with visual representations
Extensive integration of automatic computational methods
Accessible portrayal of cutting-edge visual analytics technology

For more information, you can also visit the author website, where the book's figures will be made available under the CC BY Open Access license: https: //ivda-book.de/

作者介紹

Christian Tominski is a researcher and lecturer at the Institute for Visual & Analytic Computing at the University of Rostock, Germany. He received doctoral (Dr.-Ing.) and post-doctoral (Dr.-Ing. habil.) degrees in 2006 and 2015, respectively. His main research interests are in visualization of and interaction with data. He is particularly interested in effective and efficient techniques for interactively exploring and editing complex data. Christian has published numerous papers on new visualization and interaction techniques for multivariate data, temporal data, geo-spatial data, and graphs. He co-authored two books on the visualization of time-oriented data in 2011 and on interaction for visualization in 2015. Christian has developed several visualization systems and tools, including the LandVis system for spatio-temporal health data, the VisAxes tool for time-oriented data, and the CGV system for coordinated graph visualization.
Heidrun Schumann is a professor at the University of Rostock, Germany, where she is heading the Chair of Computer Graphics at the Institute for Visual & Analytic Computing. She received doctoral degree (Dr.-Ing.) in 1981 and post-doctoral degree (Dr.-Ing. habil.) in 1989. Her research and teaching activities cover a variety of topics related to computer graphics, including information visualization, visual analytics, and rendering. She is interested in visualizing complex data in space and time, combining visualization and terrain rendering, and facilitating visual data analysis with progressive methods. A key focus of Heidrun's work is to intertwine visual, analytic, and interactive methods for making sense of data. Heidrun published more than two hundred articles in top venues and journals. She co-authored the first German textbook on data visualization in 2000 and a textbook specifically on the visualization of time-oriented data in 2011. In 2014, Heidrun was elected as a Fellow of the Eurographics Association.