Universität Stuttgart
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Item Open Access Philosophy of action and Its relationship to interactive visualisation and Molière’s theatre(2023) Feige, Daniel M.; Weiskopf, Daniel; Dickhaut, KirstenItem Open Access Datamator : an authoring tool for creating datamations via data query decomposition(2023) Guo, Yi; Cao, Nan; Cai, Ligan; Wu, Yanqiu; Weiskopf, Daniel; Shi, Danqing; Chen, QingDatamation is designed to animate an analysis pipeline step by step, serving as an intuitive and efficient method for interpreting data analysis outcomes and facilitating easy sharing with others. However, the creation of a datamation is a difficult task that demands expertise in diverse skills. To simplify this task, we introduce Datamator, a language-oriented authoring tool developed to support datamation generation. In this system, we develop a data query analyzer that enables users to generate an initial datamation effortlessly by inputting a data question in natural language. Then, the datamation is displayed in an interactive editor that affords users the ability to both edit the analysis progression and delve into the specifics of each step undertaken. Notably, the Datamator incorporates a novel calibration network that is able to optimize the outputs of the query decomposition network using a small amount of user feedback. To demonstrate the effectiveness of Datamator, we conduct a series of evaluations including performance validation, a controlled user study, and expert interviews.Item Open Access Visual analytics of multivariate intensive care time series data(2022) Brich, N.; Schulz, Christoph; Peter, J.; Klingert, W.; Schenk, M.; Weiskopf, Daniel; Krone, M.We present an approach for visual analysis of high‐dimensional measurement data with varying sampling rates as routinely recorded in intensive care units. In intensive care, most assessments not only depend on one single measurement but a plethora of mixed measurements over time. Even for trained experts, efficient and accurate analysis of such multivariate data remains a challenging task. We present a linked‐view post hoc visual analytics application that reduces data complexity by combining projection‐based time curves for overview with small multiples for details on demand. Our approach supports not only the analysis of individual patients but also of ensembles by adapting existing techniques using non‐parametric statistics. We evaluated the effectiveness and acceptance of our approach through expert feedback with domain scientists from the surgical department using real‐world data: a post‐surgery study performed on a porcine surrogate model to identify parameters suitable for diagnosing and prognosticating the volume state, and clinical data from a public database. The results show that our approach allows for detailed analysis of changes in patient state while also summarizing the temporal development of the overall condition.Item Open Access Impact of gaze uncertainty on AOIs in information visualisations(2022) Wang, Yao; Koch, Maurice; Bâce, Mihai; Weiskopf, Daniel; Bulling, AndreasGaze-based analysis of areas of interest (AOIs) is widely used in information visualisation research to understand how people explore visualisations or assess the quality of visualisations concerning key characteristics such as memorability. However, nearby AOIs in visualisations amplify the uncertainty caused by the gaze estimation error, which strongly influences the mapping between gaze samples or fixations and different AOIs. We contribute a novel investigation into gaze uncertainty and quantify its impact on AOI-based analysis on visualisations using two novel metrics: the Flipping Candidate Rate (FCR) and Hit Any AOI Rate (HAAR). Our analysis of 40 real-world visualisations, including human gaze and AOI annotations, shows that gaze uncertainty frequently and significantly impacts the analysis conducted in AOI-based studies. Moreover, we analysed four visualisation types and found that bar and scatter plots are usually designed in a way that causes more uncertainty than line and pie plots in gaze-based analysis.Item Open Access Group diagrams for simplified representation of scanpaths(2023) Schäfer, Peter; Rodrigues, Nils; Weiskopf, Daniel; Storandt, SabineWe instrument Group Diagrams (GDs) to reduce clutter in sets of eye-tracking scanpaths. Group Diagrams consist of trajectory subsets that cover, or represent, the whole set of trajectories with respect to some distance measure and an adjustable distance threshold. The original GDs allow for an application of various distance measures. We implement the GD framework and evaluate it on scanpaths that were collected by a former user study on public transit maps. We find that the Fréchet distance is the most appropriate measure to get meaningful results, yet it is flexible enough to cover outliers. We discuss several implementation-specific challenges and improve the scalability of the algorithm. To evaluate our results, we conducted a qualitative study with a group of eye-tracking experts. Finally, we note that our enhancements are also beneficial within the original problem setting, suggesting that our approach might be applicable to various types of input data.Item Open Access A depth-cueing scheme based on linear transformations in tristimulus space(2002) Weiskopf, Daniel; Ertl, ThomasWe propose a generic and flexible depth-cueing scheme which subsumes many well-known and new color-based depth-cueing approaches. In particular, it includes standard intensity depth-cueing and rather neglected pure saturation depth-cueing. A couple of new combinations and variations of depth cues are presented. Their usefulness is demonstrated in many different fields of application, reaching from non-photorealistic rendering to information visualization. In addition to cues based on a geometric concept of depth, an abstract visualization approach in the form of semantic depth-cueing is proposed. Our depth-cueing scheme is based on linear transformations in the 3D tristimulus space of colors and on weighted sums of colors. Since all of the required operations are supported by contemporary consumer graphics hardware, the depth-cueing scheme can be implemented without performance cutbacks. Therefore, any real-time rendering application can be enriched by sophisticated depth-cueing.Item Open Access Visual analytics for nonlinear programming in robot motion planning(2022) Hägele, David; Abdelaal, Moataz; Oguz, Ozgur S.; Toussaint, Marc; Weiskopf, DanielNonlinear programming is a complex methodology where a problem is mathematically expressed in terms of optimality while imposing constraints on feasibility. Such problems are formulated by humans and solved by optimization algorithms. We support domain experts in their challenging tasks of understanding and troubleshooting optimization runs of intricate and high-dimensional nonlinear programs through a visual analytics system. The system was designed for our collaborators’ robot motion planning problems, but is domain agnostic in most parts of the visualizations. It allows for an exploration of the iterative solving process of a nonlinear program through several linked views of the computational process. We give insights into this design study, demonstrate our system for selected real-world cases, and discuss the extension of visualization and visual analytics methods for nonlinear programming.Item Open Access Efficient and robust background modeling with dynamic mode decomposition(2022) Krake, Tim; Bruhn, Andrés; Eberhardt, Bernhard; Weiskopf, DanielA large number of modern video background modeling algorithms deal with computational costly minimization problems that often need parameter adjustments. While in most cases spatial and temporal constraints are added artificially to the minimization process, our approach is to exploit Dynamic Mode Decomposition (DMD), a spectral decomposition technique that naturally extracts spatio-temporal patterns from data. Applied to video data, DMD can compute background models. However, the original DMD algorithm for background modeling is neither efficient nor robust. In this paper, we present an equivalent reformulation with constraints leading to a more suitable decomposition into fore- and background. Due to the reformulation, which uses sparse and low-dimensional structures, an efficient and robust algorithm is derived that computes accurate background models. Moreover, we show how our approach can be extended to RGB data, data with periodic parts, and streaming data enabling a versatile use.Item Open Access Uncertainty visualization : concepts, methods, and applications in biological data visualization(2022) Weiskopf, DanielThis paper provides an overview of uncertainty visualization in general, along with specific examples of applications in bioinformatics. Starting from a processing and interaction pipeline of visualization, components are discussed that are relevant for handling and visualizing uncertainty introduced with the original data and at later stages in the pipeline, which shows the importance of making the stages of the pipeline aware of uncertainty and allowing them to propagate uncertainty. We detail concepts and methods for visual mappings of uncertainty, distinguishing between explicit and implict representations of distributions, different ways to show summary statistics, and combined or hybrid visualizations. The basic concepts are illustrated for several examples of graph visualization under uncertainty. Finally, this review paper discusses implications for the visualization of biological data and future research directions.Item Open Access Visual analysis of fitness landscapes in architectural design optimization(2024) Abdelaal, Moataz; Galuschka, Marcel; Zorn, Max; Kannenberg, Fabian; Menges, Achim; Wortmann, Thomas; Weiskopf, Daniel; Kurzhals, KunoIn architectural design optimization, fitness landscapes are used to visualize design space parameters in relation to one or more objective functions for which they are being optimized. In our design study with domain experts, we developed a visual analytics framework for exploring and analyzing fitness landscapes spanning data, projection, and visualization layers. Within the data layer, we employ two surrogate models and three sampling strategies to efficiently generate a wide array of landscapes. On the projection layer, we use star coordinates and UMAP as two alternative methods for obtaining a 2D embedding of the design space. Our interactive user interface can visualize fitness landscapes as a continuous density map or a discrete glyph-based map. We investigate the influence of surrogate models and sampling strategies on the resulting fitness landscapes in a parameter study. Additionally, we present findings from a user study ( N = 12), revealing how experts’ preferences regarding projection methods and visual representations may be influenced by their level of expertise, characteristics of the techniques, and the specific task at hand. Furthermore, we demonstrate the usability and usefulness of our framework by a case study from the architecture domain, involving one domain expert.