October 18, 2022; Christina Warren

At IEEE VIS 2022, David Hägele, Tim Krake and Daniel Weiskopf were awarded the Best Paper Award for their paper "Uncertainty-Aware Multidimensional Scaling". The IEEE VIS is one of the world's largest and most important conferences in the field of visualization and was held this year as a hybrid event in Oklahoma City, USA. With the Best Paper Award, the conference honors outstanding papers from the pool of accepted papers.



We present an extension of multidimensional scaling (MDS) to uncertain data, facilitating uncertainty visualization of multidimensional data. Our approach uses local projection operators that map high-dimensional random vectors to low-dimensional space to formulate a generalized stress. In this way, our generic model supports arbitrary distributions and various stress types. We use our uncertainty-aware multidimensional scaling (UAMDS) concept to derive a formulation for the case of normally distributed random vectors and a squared stress. The resulting minimization problem is numerically solved via gradient descent. We complement UAMDS by additional visualization techniques that address the sensitivity and trustworthiness of dimensionality reduction under uncertainty. With several examples, we demonstrate the usefulness of our approach and the importance of uncertainty-aware techniques.

UAMDS teaser

 Fig.1: Uncertainty-Aware Multidimensional Scaling (UAMDS) for increasing levels of uncertainty. The top row shows 4-dimensional data sets consisting of 6 entries (color-coded). The left data set has no uncertainty, the middle data set models one entry as a normally distributed random vector, and the right data set entirely consists of multivariate normal distributions. The bottom row shows the respective UAMDS projection, where the isolines indicate the 25th to 75th percentile range of the projected (normal) distributions. The projected points of the left projection are shown in faded color in the other two plots to indicate the change due to uncertainty.


Further SFB-TRR 161 Contirbutions to IEEE VIS 2022

Both at IEE VIS and the workshops held in conjunction with IEEE VIS, serveral papers by SFB-TRR 161 researchers were accepted:

Links:  IEEE VIS 2022 Conference

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