Oliver Bieh-Zimmert

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Epidemiology requires the analysis and visualization of massive data sets. The field of cancer statistics in particular is facing the challenging task of visualizing a large data set that contains a wide range of available dimensions. The existing work of epidemiologists has been time-consuming because of visualization techniques that could not be scaled to(More)
Scaling data visualizations to represent large data sets remains one of the top challenges from the last decade. The fast growing amount of data is facing limitations of human perception and of technology as bottlenecks to exploring hidden patterns. This literature review summarizes the boundaries of visual scalability and their influencing factors,(More)
Generating the maximum number of visual patterns by uncovering the entire space of possible visual designs remains a challenge within the construction process of information visualization. Users interact with different mindsets consisting of design, data analysis, application development, and hardware resource usage. Therefore, they desire a flexible and(More)
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