Universität Stuttgart
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Item 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 Local bilinear computation of Jacobi sets(2022) Klötzl, Daniel; Krake, Tim; Zhou, Youjia; Hotz, Ingrid; Wang, Bei; Weiskopf, DanielWe propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.Item Open Access Hagrid : using Hilbert and Gosper curves to gridify scatterplots(2022) Cutura, Rene; Morariu, Cristina; Cheng, Zhanglin; Wang, Yunhai; Weiskopf, Daniel; Sedlmair, MichaelA common enhancement of scatterplots represents points as small multiples, glyphs, or thumbnail images. As this encoding often results in overlaps, a general strategy is to alter the position of the data points, for instance, to a grid-like structure. Previous approaches rely on solving expensive optimization problems or on dividing the space that alter the global structure of the scatterplot. To find a good balance between efficiency and neighborhood and layout preservation, we propose Hagrid , a technique that uses space-filling curves (SFCs) to “gridify” a scatterplot without employing expensive collision detection and handling mechanisms. Using SFCs ensures that the points are plotted close to their original position, retaining approximately the same global structure. The resulting scatterplot is mapped onto a rectangular or hexagonal grid, using Hilbert and Gosper curves. We discuss and evaluate the theoretic runtime of our approach and quantitatively compare our approach to three state-of-the-art gridifying approaches, DGrid , Small multiples with gaps SMWG , and CorrelatedMultiples CMDS , in an evaluation comprising 339 scatterplots. Here, we compute several quality measures for neighborhood preservation together with an analysis of the actual runtimes. The main results show that, compared to the best other technique, Hagrid is faster by a factor of four, while achieving similar or even better quality of the gridified layout. Due to its computational efficiency, our approach also allows novel applications of gridifying approaches in interactive settings, such as removing local overlap upon hovering over a scatterplot.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 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 mint : integrating scientific visualizations into virtual reality(2024) Geringer, Sergej; Geiselhart, Florian; Bäuerle, Alex; Dec, Dominik; Odenthal, Olivia; Reina, Guido; Ropinski, Timo; Weiskopf, DanielWe present an image-based approach to integrate state-of-the-art scientific visualization into virtual reality (VR) environments: the mint visualization/VR inter-operation system. We enable the integration of visualization algorithms from within their software frameworks directly into VR without the need to explicitly port visualization implementations to the underlying VR framework—thus retaining their capabilities, specializations, and optimizations. Consequently, our approach also facilitates enriching VR-based scientific data exploration with established or novel VR immersion and interaction techniques available in VR authoring tools. The separation of concerns enables researchers and users in different domains, like virtual immersive environments, immersive analytics, and scientific visualization, to independently work with existing software suitable for their domain while being able to interface with one another easily. We present our system architecture and inter-operation protocol (mint), an example of a collaborative VR environment implemented in the Unity engine (VRAUKE), as well as the integration of the protocol for the visualization frameworks Inviwo, MegaMol, and ParaView. Our implementation is publicly available as open-source software.