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Visualization of Uncertain Scalar Data Sets

As numerical simulation processes often suffer from erroneous or incomplete physical measurement input data or error sources in the utilized algorithm, the resulting data sets are often affected by a significant degree of uncertainty and cannot be regarded as a reliable source for correct interpretations. The PhD thesis provides significant contributions to the research field of uncertainty visualization and proposes several novel algorithms, allowing a more comprehensive visualization and interpretation of multi-dimensional uncertain scalar data sets.