Abbas, Mostafa ; Ullah, Ehsan ; Baggag, Abdelkader ; Bensmail, Halima ; Sedlmair, Michael ; Aupetit, Michael: ClustRank: A Visual Quality Measure Trained on Perceptual Data for Sorting Scatterplots by Cluster Patterns (Technical Report Nr. arXiv:2106.00599) : arXiv preprint, 2021
Zusammenfassung
Visual quality measures (VQMs) are designed to support analysts by automatically detecting and quantifying patterns in visualizations. We propose a new data-driven technique called ClustRank that allows to rank scatterplots according to visible grouping patterns. Our model first encodes scatterplots in the parametric space of a Gaussian Mixture Model, and then uses a classifier trained on human judgment data to estimate the perceptual complexity of grouping patterns. The numbers of initial mixture components and final combined groups determine the rank of the scatterplot. ClustRank improves on existing VQM techniques by mimicking human judgments on two-Gaussian cluster patterns, and gives more accuracy when ranking general cluster patterns in scatterplots. We demonstrate its benefit by analyzing kinship data for genome-wide association studies, a domain in which experts rely on the visual analysis of large sets of scatterplots. We make the three benchmark datasets and the ClustRank VQM available for practical use and further improvements.BibTeX
Achberger, Alexander ; Heyen, Frank ; Vidackovic, Kresimir ; Sedlmair, Michael: PropellerHand: A Hand-Mounted, Propeller-Based Force Feedback Device. In: International Symposium on Visual Information Communication and Interaction (VINCI), International Symposium on Visual Information Communication and Interaction (VINCI) : ACM, 2021, S. 4:1--4:8
Zusammenfassung
Immersive analytics is a fast growing field that is often applied in virtual reality (VR). VR environments often lack immersion due to missing sensory feedback when interacting with data. Existing haptic devices are often expensive, stationary, or occupy the user’s hand, preventing them from grasping objects or using a controller. We propose PropellerHand, an ungrounded hand-mounted haptic device with two rotatable propellers, that allows exerting forces on the hand without obstructing hand use. PropellerHand is able to simulate feedback such as weight and torque by generating thrust up to 11 N in 2-DOF and a torque of 1.87 Nm in 2-DOF. Its design builds on our experience from quantitative and qualitative experiments with different form factors and parts. We evaluated our final version through a qualitative user study in various VR scenarios that required participants to manipulate virtual objects in different ways, while changing between torques and directional forces. Results show that PropellerHand improves users’ immersion in virtual reality.BibTeX
Achberger, Alexander ; Aust, Fabian ; Pohlandt, Daniel ; Vidackovic, Kresimir ; Sedlmair, Michael: STRIVE: String-Based Force Feedback for Automotive Engineering. In: ACM Symposium on User Interface Software and Technology (UIST), ACM Symposium on User Interface Software and Technology (UIST), 2021, S. 841--853
Zusammenfassung
The large potential of force feedback devices for interacting in Virtual Reality (VR) has been illustrated in a plethora of research prototypes. Yet, these devices are still rarely used in practice and it remains an open challenge how to move this research into practice. To that end, we contribute a participatory design study on the use of haptic feedback devices in the automotive industry. Based on a 10-month observing process with 13 engineers, we developed STRIVE, a string-based haptic feedback device. In addition to the design of STRIVE, this process led to a set of requirements for introducing haptic devices into industrial settings, which center around a need for flexibility regarding forces, comfort, and mobility. We evaluated STRIVE with 16 engineers in five different day-to-day automotive VR use cases. The main results show an increased level of trust and perceived safety as well as further challenges towards moving haptics research into practice.BibTeX
Anzt, Hartwig ; Bach, Felix ; Druskat, Stephan ; Löffler, Frank ; Loewe, Axel ; Renard, Bernhard Y. ; Seemann, Gunnar ; Struck, Alexander ; u. a.: An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action. In: F1000Research, F1000Research. Bd. 9, F1000 Research Ltd (2021), S. 295
BibTeX
Armanious, Karim ; Abdulatif, Sherif ; Shi, Wenbin ; Salian, Shashank ; Küstner, Thomas ; Weiskopf, Daniel ; Hepp, Tobias ; Gatidis, Sergios ; u. a.: Age-Net: An MRI-Based Iterative Framework for Brain Biological Age Estimation. In: IEEE Transactions on Medical Imaging, IEEE Transactions on Medical Imaging. Bd. 40 (2021), Nr. 7, S. 1778–1791
Zusammenfassung
The concept of biological age (BA) - although important in clinical practice - is hard to grasp mainly due to the lack of a clearly defined reference standard. For specific applications, especially in pediatrics, medical image data are used for BA estimation in a routine clinical context. Beyond this young age group, BA estimation is mostly restricted to whole-body assessment using non-imaging indicators such as blood biomarkers, genetic and cellular data. However, various organ systems may exhibit different aging characteristics due to lifestyle and genetic factors. Thus, a whole-body assessment of the BA does not reflect the deviations of aging behavior between organs. To this end, we propose a new imaging-based framework for organ-specific BA estimation. In this initial study we focus mainly on brain MRI. As a first step, we introduce a chronological age (CA) estimation framework using deep convolutional neural networks (Age-Net). We quantitatively assess the performance of this framework in comparison to existing state-of-the-art CA estimation approaches. Furthermore, we expand upon Age-Net with a novel iterative data-cleaning algorithm to segregate atypical-aging patients (BA ≉ CA) from the given population. We hypothesize that the remaining population should approximate the true BA behavior. We apply the proposed methodology on a brain magnetic resonance image (MRI) dataset containing healthy individuals as well as Alzheimer’s patients with different dementia ratings. We demonstrate the correlation between the predicted BAs and the expected cognitive deterioration in Alzheimer’s patients. A statistical and visualization-based analysis has provided evidence regarding the potential and current challenges of the proposed methodology.BibTeX
Beck, Samuel ; Frank, Sebastian ; Hakamian, Alireza ; Merino, Leonel ; van Hoorn, André: TransVis: Using Visualizations and Chatbots for Supporting Transient Behavior in Microservice Systems, 2021 Working Conference on Software Visualization (VISSOFT) : IEEE, 2021 — ISBN 978-1-6654-3144-6
Zusammenfassung
In a microservice system, runtime changes such as failures, deployments, or self-adaptation can trigger the system to transition from one steady state to another, i.e., exhibiting transient behavior.
To assess a system's quality, it is imperative that this transient behavior is specified in non-functional requirements and that stakeholders can analyze whether these requirements are met.
Yet, there is little support for either specifying transient behavior as a non-functional requirement or analyzing how such a requirement is met in production.
We aim to make these two tasks more accessible by utilizing novel human-computer interaction methods.
To this end, we developed TransVis, an approach for specifying and analyzing transient behavior based on chatbot interactions and visualizations of the systems' resilience.
We examined the effectiveness of our approach by conducting an exploratory expert study on a prototypical implementation.
The study revealed that the developed visualizations are effective for specifying and exploring transient behavior.
Participants found especially helpful the feature to compare specifications with the actual behavior.
However, the integration of a chatbot did not prove effective for our use cases.
In conclusion, our approach is capable of supporting stakeholders in the exploration and specification of transient behavior.BibTeX
Bernard, Jürgen ; Hutter, Marco ; Zeppelzauer, Matthias ; Sedlmair, Michael ; Munzner, Tamara: ProSeCo: Visual analysis of class separation measures and dataset characteristics. In: Computers & Graphics, Computers & Graphics. Bd. 96 (2021), S. 48–60
Zusammenfassung
Class separation is an important concept in machine learning and visual analytics. We address the visual analysis of class separation measures for both high-dimensional data and its corresponding projections into 2D through dimensionality reduction (DR) methods. Although a plethora of separation measures have been proposed, it is difficult to compare class separation between multiple datasets with different characteristics, multiple separation measures, and multiple DR methods. We present ProSeCo, an interactive visualization approach to support comparison between up to 20 class separation measures and up to 4 DR methods, with respect to any of 7 dataset characteristics: dataset size, dataset dimensions, class counts, class size variability, class size skewness, outlieriness, and real-world vs. synthetically generated data. ProSeCo supports (1) comparing across measures, (2) comparing high-dimensional to dimensionally-reduced 2D data across measures, (3) comparing between different DR methods across measures, (4) partitioning with respect to a dataset characteristic, (5) comparing partitions for a selected characteristic across measures, and (6) inspecting individual datasets in detail. We demonstrate the utility of ProSeCo in two usage scenarios, using datasets 1 posted at https://osf.io/epcf9/.BibTeX
Bernard, Jürgen ; Hutter, Marco ; Sedlmair, Michael ; Zeppelzauer, Matthias ; Munzner, Tamara: A Taxonomy of Property Measures to Unify Active Learning and Human-centered Approaches to Data Labeling. In: ACM Transactions on Interactive Intelligent Systems (TiiS), ACM Transactions on Interactive Intelligent Systems (TiiS). Bd. 11 (2021), Nr. 3–4, S. 1--42
Zusammenfassung
Strategies for selecting the next data instance to label, in service of generating labeled data for machine learning, have been considered separately in the machine learning literature on active learning and in the visual analytics literature on human-centered approaches. We propose a unified design space for instance selection strategies to support detailed and fine-grained analysis covering both of these perspectives. We identify a concise set of 15 properties, namely measureable characteristics of datasets or of machine learning models applied to them, that cover most of the strategies in these literatures. To quantify these properties, we introduce Property Measures (PM) as fine-grained building blocks that can be used to formalize instance selection strategies. In addition, we present a taxonomy of PMs to support the description, evaluation, and generation of PMs across four dimensions: machine learning (ML) Model Output, Instance Relations, Measure Functionality, and Measure Valence. We also create computational infrastructure to support qualitative visual data analysis: a visual analytics explainer for PMs built around an implementation of PMs using cascades of eight atomic functions. It supports eight analysis tasks, covering the analysis of datasets and ML models using visual comparison within and between PMs and groups of PMs, and over time during the interactive labeling process. We iteratively refined the PM taxonomy, the explainer, and the task abstraction in parallel with each other during a two-year formative process, and show evidence of their utility through a summative evaluation with the same infrastructure. This research builds a formal baseline for the better understanding of the commonalities and differences of instance selection strategies, which can serve as the stepping stone for the synthesis of novel strategies in future work.BibTeX
Bian, R. ; Xue, Y. ; Zhou, L. ; Zhang, J. ; Chen, B. ; Weiskopf, D. ; Wang, Y.: Implicit Multidimensional Projection of Local Subspaces. In: IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics. Bd. 27 (2021), Nr. 2, S. 1558–1568
Zusammenfassung
We propose a visualization method to understand the effect of multidimensional projection on local subspaces, using implicit function differentiation. Here, we understand the local subspace as the multidimensional local neighborhood of data points. Existing methods focus on the projection of multidimensional data points, and the neighborhood information is ignored. Our method is able to analyze the shape and directional information of the local subspace to gain more insights into the global structure of the data through the perception of local structures. Local subspaces are fitted by multidimensional ellipses that are spanned by basis vectors. An accurate and efficient vector transformation method is proposed based on analytical differentiation of multidimensional projections formulated as implicit functions. The results are visualized as glyphs and analyzed using a full set of specifically-designed interactions supported in our efficient web-based visualization tool. The usefulness of our method is demonstrated using various multi- and high-dimensional benchmark datasets. Our implicit differentiation vector transformation is evaluated through numerical comparisons; the overall method is evaluated through exploration examples and use cases.BibTeX
Blascheck, Tanja ; Bentley, Frank ; Choe, Eun Kyoung ; Horak, Tom ; Isenberg, Petra: Characterizing Glanceable Visualizations: From Perception to Behavior Change. In: Lee, B. ; Dachselt, R. ; Isenberg, P. ; Choe, E. K. (Hrsg.) ; Lee, B. ; Dachselt, R. ; Isenberg, P. ; Choe, E. K. (Hrsg.): Mobile Data Visualization, Mobile Data Visualization : Chapman and Hall/CRC, 2021, S. 151--176
BibTeX
Blascheck, Tanja ; Isenberg, Petra: A Replication Study on Glanceable Visualizations: Comparing Different
Stimulus Sizes on a Laptop Computer. In: Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application, Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application : SCITEPRESS, 2021
BibTeX
Bu, C. ; Zhang, Q. ; Wang, Q. ; Zhang, J. ; Sedlmair, M. ; Deussen, O. ; Wang, Y.: SineStream: Improving the Readability of Streamgraphs by Minimizing Sine Illusion Effects. In: IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics. Bd. 27 (2021), Nr. 2, S. 1634–1643
Zusammenfassung
In this paper, we propose SineStream, a new variant of streamgraphs that improves their readability by minimizing sine illusion effects. Such effects reflect the tendency of humans to take the orthogonal rather than the vertical distance between two curves as their distance. In SineStream, we connect the readability of streamgraphs with minimizing sine illusions and by doing so provide a perceptual foundation for their design. As the geometry of a streamgraph is controlled by its baseline (the bottom-most curve) and the ordering of the layers, we re-interpret baseline computation and layer ordering algorithms in terms of reducing sine illusion effects. For baseline computation, we improve previous methods by introducing a Gaussian weight to penalize layers with large thickness changes. For layer ordering, three design requirements are proposed and implemented through a hierarchical clustering algorithm. Quantitative experiments and user studies demonstrate that SineStream improves the readability and aesthetics of streamgraphs compared to state-of-the-art methods.BibTeX
Burch, Michael ; Huang, Weidong ; Wakefield, Mathew ; Purchase, Helen C. ; Weiskopf, Daniel ; Hua, Jie: The State of the Art in Empirical User Evaluation of Graph Visualizations. In: IEEE Access, IEEE Access. Bd. 9 (2021), S. 4173–4198
Zusammenfassung
While graph drawing focuses more on the aesthetic representation of node-link diagrams, graph visualization takes into account other visual metaphors making them useful for graph exploration tasks in information visualization and visual analytics. Although there are aesthetic graph drawing criteria that describe how a graph should be presented to make it faster and more reliably explorable, many controlled and uncontrolled empirical user studies flourished over the past years. The goal of them is to uncover how well the human user performs graph-specific tasks, in many cases compared to previously designed graph visualizations. Due to the fact that many parameters in a graph dataset as well as the visual representation of them might be varied and many user studies have been conducted in this space, a state-of-the-art survey is needed to understand evaluation results and findings to inform the future design, research, and application of graph visualizations. In this article, we classify the present literature on the topmost level into graph interpretation, graph memorability, and graph creation where the users with their tasks stand in focus of the evaluation, not the computational aspects. As another outcome of this work, we identify the white spots in this field and sketch ideas for future research directions.BibTeX
Carpendale, Sheelagh ; Isenberg, Petra ; Perin, Charles ; Blascheck, Tanja ; Daneshzand, Foroozan ; Islam, Alaul ; Currier, Katherine ; Buk, Peter ; u. a.: Mobile Visualization Design: An Ideation Method to Try. In: Lee, B. ; Dachselt, R. ; Isenberg, P. ; Choe, E. K. (Hrsg.) ; Lee, B. ; Dachselt, R. ; Isenberg, P. ; Choe, E. K. (Hrsg.): Mobile Data Visualization, Mobile Data Visualization : Chapman and Hall/CRC, 2021, S. 241--262
BibTeX
Chen, Jian ; Ling, Meng ; Li, Rui ; Isenberg, Petra ; Isenberg, Tobias ; Sedlmair, Michael ; Möller, Torsten ; Laramee, Robert S ; u. a.: VIS30K: A collection of figures and tables from IEEE visualization conference publications. In: IEEE Transactions on Visualization and Computer Graphics (TVCG), IEEE Transactions on Visualization and Computer Graphics (TVCG). Bd. 27 (2021), Nr. 9, S. 3826--3833
Zusammenfassung
We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field but also enables researchers to study the evolution of the state-of-the-art and to find relevant work based on graphical content. We describe the dataset and our semi-automatic collection process, which couples convolutional neural networks (CNN) with curation. Extracting figures and tables semi-automatically allows us to verify that no images are overlooked or extracted erroneously. To improve quality further, we engaged in a peer-search process for high-quality figures from early IEEE Visualization papers. With the resulting data, we also contribute VISImageNavigator (VIN, visimagenavigator.github.io ), a web-based tool that facilitates searching and exploring VIS30K by author names, paper keywords, title and abstract, and years.BibTeX
Cutura, Rene ; Angerbauer, Katrin ; Heyen, Frank ; Hube, Natalie ; Sedlmair, Michael: DaRt: Generative Art using Dimensionality Reduction Algorithms. In: IEEE VIS Arts Program (VISAP), IEEE VIS Arts Program (VISAP) : IEEE, 2021, S. 59--72
Zusammenfassung
Dimensionality Reduction (DR) is a popular technique that is often used in Machine Learning and Visualization communities to analyze high-dimensional data. The approach is empirically proven to be powerful for uncovering previously unseen structures in the data. While observing the results of the intermediate optimization steps of DR algorithms, we coincidently discovered the artistic beauty of the DR process. With enthusiasm for the beauty, we decided to look at DR from a generative art lens rather than their technical application aspects and use DR techniques to create artwork. Particularly, we use the optimization process to generate images, by drawing each intermediate step of the optimization process with some opacity over the previous intermediate result. As another alternative input, we used a neural-network model for face-landmark detection, to apply DR to portraits, while maintaining some facial properties, resulting in abstracted facial avatars. In this work, we provide such a collection of such artwork.BibTeX
Cutura, Rene ; Morariu, Cristina ; Cheng, Zhanglin ; Wang, Yunhai ; Weiskopf, Daniel ; Sedlmair, Michael: Hagrid — Gridify Scatterplots with Hilbert and Gosper Curves. In: The 14th International Symposium on Visual Information Communication and Interaction, The 14th International Symposium on Visual Information Communication and Interaction. Potsdam, Germany : Association for Computing Machinery, 2021 — ISBN 9781450386470, S. 1:1—1:8
Zusammenfassung
A 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.BibTeX
Eirich, Joscha ; Bonart, Jakob ; Jäckle, Dominik ; Sedlmair, Michael ; Schmid, Ute ; Fischbach, Kai ; Schreck, Tobias ; Bernard, Jürgen: IRVINE: A Design Study on Analyzing Correlation Patterns of Electrical Engines. In: IEEE Trans. Visualization and Computer Graphics (TVCG, Proc. VIS 2021), IEEE Trans. Visualization and Computer Graphics (TVCG, Proc. VIS 2021). (2021). — To appear. Best paper award
Zusammenfassung
In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the analysis of acoustic data to detect and understand previously unknown errors in the manufacturing of electrical engines. In serial manufacturing processes, signatures from acoustic data provide valuable information on how the relationship between multiple produced engines serves to detect and understand previously unknown errors. To analyze such signatures, IRVINE leverages interactive clustering and data labeling techniques, allowing users to analyze clusters of engines with similar signatures, drill down to groups of engines, and select an engine of interest. Furthermore, IRVINE allows to assign labels to engines and clusters and annotate the cause of an error in the acoustic raw measurement of an engine. Since labels and annotations represent valuable knowledge, they are conserved in a knowledge database to be available for other stakeholders. We contribute a design study, where we developed IRVINE in four main iterations with engineers from a company in the automotive sector. To validate IRVINE, we conducted a field study with six domain experts. Our results suggest a high usability and usefulness of IRVINE as part of the improvement of a real-world manufacturing process. Specifically, with IRVINE domain experts were able to label and annotate produced electrical engines more than 30% faster.BibTeX
Epstein, Daniel A ; Blascheck, Tanja ; Carpendale, Sheelagh ; Dachselt, Raimund ; Vermeulen, Jo: Challenges in Everyday Use of Mobile Visualizations. In: Lee, B. ; Dachselt, R. ; Isenberg, P. ; Choe, E. K. (Hrsg.) ; Lee, B. ; Dachselt, R. ; Isenberg, P. ; Choe, E. K. (Hrsg.): Mobile Data Visualization, Mobile Data Visualization : Chapman and Hall/CRC, 2021, S. 209--240
BibTeX
Franke, Max ; Martin, Henry ; Koch, Steffen ; Kurzhals, Kuno: Visual Analysis of Spatio-temporal Phenomena with 1D Projections. In: Computer Graphics Forum, Computer Graphics Forum. Bd. 40, The Eurographics Association and John Wiley & Sons Ltd. (2021), Nr. 3, S. 335--347
Zusammenfassung
It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.BibTeX
Frey, Steffen ; Scheller, Stefan ; Karadimitriou, Nikolaos ; Lee, Dongwon ; Reina, Guido ; Steeb, Holger ; Ertl, Thomas: Visual Analysis of Two-Phase Flow Displacement Processes in Porous Media. In: Computer Graphics Forum, Computer Graphics Forum. Bd. n/a (2021), Nr. n/a
Zusammenfassung
Abstract We developed a new visualization approach to gain a better understanding of the displacement of one fluid phase by another in porous media. This is based on a recent experimental parameter study with varying capillary numbers and viscosity ratios. We analyse the temporal evolution of characteristic values in this two-phase flow scenario and discuss how to directly compare experiments across different temporal scales. To enable spatio-temporal analysis, we introduce a new abstract visual representation showing which paths through the porous medium were occupied and for how long. These transport networks allow to assess the impact of different acting forces and they are designed to yield expressive comparability and linking to the experimental parameter space both supported by additional visual cues. This joint work of porous media experts and visualization researchers yields new insights regarding two-phase flow on the microscale, and our visualization approach contributes towards the overarching goal of the domain scientists to characterize porous media flow based on capillary numbers and viscosity ratios.BibTeX
Frieß, Florian ; Becher, Michael ; Reina, Guido ; Ertl, Thomas: Amortised Encoding for Large High-Resolution Displays. In: 2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV), 2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV), 2021, S. 53–62
Zusammenfassung
Both visual detail and a low-latency transfer of image data are required for collaborative exploration of scientific data sets across large high-resolution displays. In this work, we present an approach that reduces the resolution before the encoding and uses temporal upscaling to reconstruct the full resolution image, reducing the overall latency and the required bandwidth without significantly impacting the details perceived by observers. Our approach takes advantage of the fact that humans do not perceive the full details of moving objects by providing a perfect reconstruction for static parts of the image, while non-static parts are reconstructed with a lower quality. This strategy enables a substantial reduction of the encoding latency and the required bandwidth with barely noticeable changes in visual quality, which is crucial for collaborative analysis across display walls at different locations. Additionally, our approach can be combined with other techniques aiming to reduce the required bandwidth while keeping the quality as high as possible, such as foveated encoding. We demonstrate the reduced overall latency, the required bandwidth, as well as the high image quality using different visualisations.BibTeX
Garcia, Rafael ; Munz, Tanja ; Weiskopf, Daniel: Visual analytics tool for the interpretation of hidden states in recurrent neural networks. In: Visual Computing for Industry, Biomedicine, and Art, Visual Computing for Industry, Biomedicine, and Art. Bd. 4 (2021), Nr. 24
Zusammenfassung
In this paper, we introduce a visual analytics approach aimed at helping machine learning experts analyze the hidden states of layers in recurrent neural networks. Our technique allows the user to interactively inspect how hidden states store and process information throughout the feeding of an input sequence into the network. The technique can help answer questions, such as which parts of the input data have a higher impact on the prediction and how the model correlates each hidden state configuration with a certain output. Our visual analytics approach comprises several components: First, our input visualization shows the input sequence and how it relates to the output (using color coding). In addition, hidden states are visualized through a nonlinear projection into a 2-D visualization space using t-distributed stochastic neighbor embedding to understand the shape of the space of the hidden states. Trajectories are also employed to show the details of the evolution of the hidden state configurations. Finally, a time-multi-class heatmap matrix visualizes the evolution of the expected predictions for multi-class classifiers, and a histogram indicates the distances between the hidden states within the original space. The different visualizations are shown simultaneously in multiple views and support brushing-and-linking to facilitate the analysis of the classifications and debugging for misclassified input sequences. To demonstrate the capability of our approach, we discuss two typical use cases for long short-term memory models applied to two widely used natural language processing datasets.BibTeX
Grioui, Fairouz ; Blascheck, Tanja: Study of Heart Rate Visualizations on a Virtual Smartwatch, Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology : ACM, 2021
BibTeX
Grossmann, Nicolas ; Bernard, Jürgen ; Sedlmair, Michael ; Waldner, Manuela: Does the Layout Really Matter? A Study on Visual Model Accuracy Estimation. In: IEEE Visualization Conference (VIS, Short Paper), IEEE Visualization Conference (VIS, Short Paper), 2021, S. 61--65
Zusammenfassung
In visual interactive labeling, users iteratively assign labels to data items until the machine model reaches an acceptable accuracy. A crucial step of this process is to inspect the model's accuracy and decide whether it is necessary to label additional elements. In scenarios with no or very little labeled data, visual inspection of the predictions is required. Similarity-preserving scatterplots created through a dimensionality reduction algorithm are a common visualization that is used in these cases. Previous studies investigated the effects of layout and image complexity on tasks like labeling. However, model evaluation has not been studied systematically. We present the results of an experiment studying the influence of image complexity and visual grouping of images on model accuracy estimation. We found that users outperform traditional automated approaches when estimating a model's accuracy. Furthermore, while the complexity of images impacts the overall performance, the layout of the items in the plot has little to no effect on estimations.BibTeX
Heinemann, Moritz ; Frey, Steffen ; Tkachev, Gleb ; Straub, Alexander ; Sadlo, Filip ; Ertl, Thomas: Visual analysis of droplet dynamics in large-scale multiphase spray simulations. In: Journal of Visualization, Journal of Visualization. Bd. 24 (2021), Nr. 5, S. 943--961
Zusammenfassung
We present a data-driven visual analysis approach for the in-depth exploration of large numbers of droplets. Understanding droplet dynamics in sprays is of interest across many scientific fields for both simulation scientists and engineers. In this paper, we analyze large-scale direct numerical simulation datasets of the two-phase flow of non-Newtonian jets. Our interactive visual analysis approach comprises various dedicated exploration modalities that are supplemented by directly linking to ParaView. This hybrid setup supports a detailed investigation of droplets, both in the spatial domain and in terms of physical quantities . Considering a large variety of extracted physical quantities for each droplet enables investigating different aspects of interest in our data. To get an overview of different types of characteristic behaviors, we cluster massive numbers of droplets to analyze different types of occurring behaviors via domain-specific pre-aggregation, as well as different methods and parameters. Extraordinary temporal patterns are of high interest, especially to investigate edge cases and detect potential simulation issues. For this, we use a neural network-based approach to predict the development of these physical quantities and identify irregularly advected droplets.BibTeX
Hube, Natalie ; Angerbauer, Katrin ; Pohlandt, Daniel ; Vidačković, Krešimir ; Sedlmair, Michael: VR Collaboration in Large Companies: An Interview Study on the Role of Avatars. In: IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) : IEEE, 2021, S. 139--144
Zusammenfassung
Collaboration is essential in companies and often physical presence is required, thus, more and more Virtual Reality (VR) systems are used to work together remotely. To support social interaction, human representations in form of avatars are used in collaborative virtual environment (CVE) tools. However, up to now, the avatar representations often are limited in their design and functionality, which may hinder effective collaboration. In our interview study, we explored the status quo of VR collaboration in a large automotive company setting with a special focus on the role of avatars. We collected inter-view data from 21 participants, from which we identified challenges of current avatar representations used in our setting. Based on these findings, we discuss design suggestions for avatars in a company setting, which aim to improve social interaction. As opposed to state-of-the-art research, we found that users within the context of a large automotive company have an altered need with respect to avatar representations.BibTeX
Huth, Franziska ; Awad-Mohammed, Miriam ; Knittel, Johannes ; Blascheck, Tanja ; Isenberg, Petra: Online Study of Word-Sized Visualizations in Social Media. In: Byška, J. ; Jänicke, S. ; Schmidt, J. (Hrsg.) ; Byška, J. ; Jänicke, S. ; Schmidt, J. (Hrsg.): EuroVis 2021 - Posters, EuroVis 2021 - Posters : The Eurographics Association, 2021 — ISBN 978-3-03868-144-1
BibTeX
Huth, Franziska ; Blascheck, Tanja ; Koch, Steffen ; Utz, Sonja ; Ertl, Thomas: Word-sized Visualizations for Exploring Discussion Diversity in Social Media. In: Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Bd. 3 IVAPP : SciTePress, 2021 — ISBN 978-989-758-488-6, S. 256–265
Zusammenfassung
In this paper, we explore the design space of word-sized visualizations—small graphics, usually the same size as a word, that visualize data in or related to a text—for displaying and exploring categories in social media feeds such as Twitter streams. Social media contributions are typically microposts, which allow us to attach word-sized visualizations to show category assignment, diversity, or development. We consider and combine word-sized visualizations made up of basic marks and visual variables, existing word-sized visualization concepts, as well as large text visualizations. In an application example we show how word-sized visualizations can evince context changes within a discussion on Twitter and reveal topic diversity.BibTeX
Hägele, David ; Abdelaal, Moataz ; Oguz, Ozgur S. ; Toussaint, Marc ; Weiskopf, Daniel: Visual analytics for nonlinear programming in robot motion planning. In: Journal of Visualization, Journal of Visualization. (2021)
Zusammenfassung
Nonlinear 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.BibTeX
Ibrahim, Mohamed ; Rautek, Peter ; Reina, Guido ; Agus, Marco ; Hadwiger, Markus: Probabilistic Occlusion Culling using Confidence Maps for High-Quality Rendering of Large Particle Data. In: IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics., Institute of Electrical and Electronics Engineers (IEEE) (2021), S. 1--1
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Kinkeldey, Christoph ; Fekete, Jean-Daniel ; Blascheck, Tanja ; Isenberg, Petra: BitConduite: Exploratory Visual Analysis of Entity Activity on the Bitcoin Network. In: IEEE Computer Graphics and Applications, IEEE Computer Graphics and Applications. (2021)
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Knabben, Moritz ; Baumann, Martin ; Blascheck, Tanja ; Ertl, Thomas ; Koch, Steffen: Visualizing Temporal-Thematic Patterns in Text Collections. In: Andres, B. ; Campen, M. ; Sedlmair, M. (Hrsg.) ; Andres, B. ; Campen, M. ; Sedlmair, M. (Hrsg.): Vision, Modeling, and Visualization, Vision, Modeling, and Visualization : The Eurographics Association, 2021 — ISBN 978-3-03868-161-8, S. 9–16
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Knippers, Jan ; Kropp, Cordula ; Menges, Achim ; Sawodny, Oliver ; Weiskopf, Daniel: Integratives computerbasiertes Planen und Bauen: Architektur digital neu denken. In: Bautechnik, Bautechnik. Bd. 98, Wiley (2021), Nr. 3, S. 194--207
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Knittel, Johannes ; Koch, Steffen ; Ertl, Thomas: ELSKE: Efficient Large-Scale Keyphrase Extraction. In: arXiv preprint arXiv:2102.05700, arXiv preprint arXiv:2102.05700. (2021)
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Knittel, Johannes ; Koch, Steffen ; Ertl, Thomas: Efficient Sparse Spherical K-Means for Document Clustering. In: Proceedings of the 21st ACM Symposium on Document Engineering, Proceedings of the 21st ACM Symposium on Document Engineering. Limerick, Ireland : Association for Computing Machinery, 2021 — ISBN 9781450385961
Zusammenfassung
Spherical k-Means is frequently used to cluster document collections because it performs reasonably well in many settings and is computationally efficient. However, the time complexity increases linearly with the number of clusters k, which limits the suitability of the algorithm for larger values of k depending on the size of the collection. Optimizations targeted at the Euclidean k-Means algorithm largely do not apply because the cosine distance is not a metric. We therefore propose an efficient indexing structure to improve the scalability of Spherical k-Means with respect to k. Our approach exploits the sparsity of the input vectors and the convergence behavior of k-Means to reduce the number of comparisons on each iteration significantly.BibTeX
Knittel, Johannes ; Lalama, Andres ; Koch, Steffen ; Ertl, Thomas: Visual Neural Decomposition to Explain Multivariate Data Sets. In: IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics. Bd. 27 (2021), Nr. 2, S. 1374–1384
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Krake, Tim ; Reinhardt, Stefan ; Hlawatsch, Marcel ; Eberhardt, Bernhard ; Weiskopf, Daniel: Visualization and Selection of Dynamic Mode Decomposition Components for Unsteady Flow. In: Visual Informatics, Visual Informatics. Bd. 5 (2021), Nr. 3, S. 15–27
Zusammenfassung
Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data. Conceptually, DMD performs a low-dimensional spectral decomposition of the data into the following components: the modes, called DMD modes, encode the spatial contribution of the decomposition, whereas the DMD amplitudes specify their impact. Each associated eigenvalue, referred to as DMD eigenvalue, characterizes the frequency and growth rate of the DMD mode. In this paper, we demonstrate how the components of DMD can be utilized to obtain temporal and spatial information from time-dependent flow fields. We begin with the theoretical background of DMD and its application to unsteady flow. Next, we examine the conventional process with DMD mathematically and put it in relationship to the discrete Fourier transform. Our analysis shows that the current use of DMD components has several drawbacks. To resolve these problems we adjust the components and provide new and meaningful insights into the decomposition: we show that our improved components capture the spatio-temporal patterns of the flow better. Moreover, we remove redundancies in the decomposition and clarify the interplay between components, allowing users to understand the impact of components. These new representations, which respect the spatio-temporal character of DMD, enable two clustering methods that segment the flow into physically relevant sections and can therefore be used for the selection of DMD components. With a number of typical examples, we demonstrate that the combination of these techniques allows new insights with DMD for unsteady flow.BibTeX
Kraus, Matthias ; Klein, Karsten ; Fuchs, Johannes ; Keim, Daniel A ; Schreiber, Falk ; Sedlmair, Michael: The Value of Immersive Visualization. In: IEEE Computer Graphics and Applications (CG&A), IEEE Computer Graphics and Applications (CG&A). Bd. 41 (2021), Nr. 4, S. 125–132
Zusammenfassung
In recent years, research on immersive environments has experienced a new wave of interest, and immersive analytics has been established as a new research field. Every year, a vast amount of different techniques, applications, and user studies are published that focus on employing immersive environments for visualizing and analyzing data. Nevertheless, immersive analytics is still a relatively unexplored field that needs more basic research in many aspects and is still viewed with skepticism. Rightly so, because in our opinion, many researchers do not fully exploit the possibilities offered by immersive environments and, on the contrary, sometimes even overestimate the power of immersive visualizations. Although a growing body of papers has demonstrated individual advantages of immersive analytics for specific tasks and problems, the general benefit of using immersive environments for effective analytic tasks remains controversial. In this article, we reflect on when and how immersion may be appropriate for the analysis and present four guiding scenarios. We report on our experiences, discuss the landscape of assessment strategies, and point out the directions where we believe immersive visualizations have the greatest potential.BibTeX
Krauter, Christian ; Vogelsang, Jonas ; Calepso, Aimee Sousa ; Angerbauer, Katrin ; Sedlmair, Michael: Don’t Catch It: An Interactive Virtual-Reality Environment to Learn About COVID-19 Measures Using Gamification Elements. In: Mensch und Computer, Mensch und Computer : ACM, 2021, S. 593--596
Zusammenfassung
The world is still under the influence of the COVID-19 pandemic. Even though vaccines are deployed as rapidly as possible, it is still necessary to use other measures to reduce the spread of the virus. Measures such as social distancing or wearing a mask receive a lot of criticism. Therefore, we want to demonstrate a serious game to help the players understand these measures better and show them why they are still necessary. The player of the game has to avoid other agents to keep their risk of a COVID-19 infection low. The game uses Virtual Reality through a Head-Mounted-Display to deliver an immersive and enjoyable experience. Gamification elements are used to engage the user with the game while they explore various environments. We also implemented visualizations that help the user with social distancing.BibTeX
Ling, Meng ; Chen, Jian ; Möller, Torsten ; Isenberg, Petra ; Isenberg, Tobias ; Sedlmair, Michael ; Laramee, Robert S ; Shen, Han-Wei ; u. a.: Document Domain Randomization for Deep Learning Document Layout Extraction. In: Document Analysis and Recognition (ICDAR), Document Analysis and Recognition (ICDAR) : Springer International Publishing, 2021 — ISBN 978-3-030-86549-8, S. 497--513
Zusammenfassung
We present document domain randomization (DDR), the first successful transfer of convolutional neural networks (CNNs) trained only on graphically rendered pseudo-paper pages to real-world document segmentation. DDR renders pseudo-document pages by modeling randomized textual and non-textual contents of interest, with user-defined layout and font styles to support joint learning of fine-grained classes. We demonstrate competitive results using our DDR approach to extract nine document classes from the benchmark CS-150 and papers published in two domains, namely annual meetings of Association for Computational Linguistics (ACL) and IEEE Visualization (VIS). We compare DDR to conditions of style mismatch, fewer or more noisy samples that are more easily obtained in the real world. We show that high-fidelity semantic information is not necessary to label semantic classes but style mismatch between train and test can lower model accuracy. Using smaller training samples had a slightly detrimental effect. Finally, network models still achieved high test accuracy when correct labels are diluted towards confusing labels; this behavior hold across several classes.BibTeX
Lu, K. ; Feng, M. ; Chen, X. ; Sedlmair, M. ; Deussen, O. ; Lischinski, D. ; Cheng, Z. ; Wang, Y.: Palettailor: Discriminable Colorization for Categorical Data. In: IEEE Transactions on Visualization & Computer Graphics, IEEE Transactions on Visualization & Computer Graphics. Bd. 27. Los Alamitos, CA, USA, IEEE Computer Society (2021), Nr. 02, S. 475–484
Zusammenfassung
We present an integrated approach for creating and assigning color palettes to different visualizations such as multi-class scatterplots, line, and bar charts. While other methods separate the creation of colors from their assignment, our approach takes data characteristics into account to produce color palettes, which are then assigned in a way that fosters better visual discrimination of classes. To do so, we use a customized optimization based on simulated annealing to maximize the combination of three carefully designed color scoring functions: point distinctness, name difference, and color discrimination. We compare our approach to state-of-the-art palettes with a controlled user study for scatterplots and line charts, furthermore we performed a case study. Our results show that Palettailor, as a fully-automated approach, generates color palettes with a higher discrimination quality than existing approaches. The efficiency of our optimization allows us also to incorporate user modifications into the color selection process.BibTeX
Mehl, Lukas ; Beschle, Cedric ; Barth, Andrea ; Bruhn, Andrés: An Anisotropic Selection Scheme for Variational Optical Flow Methods with Order-Adaptive Regularisation. In: Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), Proc. International Conference on Scale Space and Variational Methods in Computer Vision (SSVM) : Springer, 2021, S. 140--152
Zusammenfassung
Approaches based on order-adaptive regularisation belong to the most accurate variational methods for computing the optical flow. By locally deciding between first- and second-order regularisation, they are applicable to scenes with both fronto-parallel and ego-motion. So far, however, existing order-adaptive methods have a decisive drawback. While the involved first- and second-order smoothness terms already make use of anisotropic concepts, the underlying selection process itself is still isotropic in that sense that it locally chooses the same regularisation order for all directions. In our paper, we address this shortcoming. We propose a generalised order-adaptive approach that allows to select the local regularisation order for each direction individually. To this end, we split the order-adaptive regularisation across and along the locally dominant direction and perform an energy competition for each direction separately. This in turn offers another advantage. Since the parameters can be chosen differently for both directions, the approach allows for a better adaption to the underlying scene. Experiments for MPI Sintel and KITTI 2015 demonstrate the usefulness of our approach. They not only show improvements compared to an isotropic selection scheme. They also make explicit that our approach is able to improve the results from state-of-the-art learning-based approaches, if applied as a final refinement step – thereby achieving top results in both benchmarks.BibTeX
Morariu, Cristina ; Bibal, Adrien ; Cutura, Rene ; Frenay, Benoit ; Sedlmair, Michael: DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality (Technical Report Nr. arXiv:2105.09275) : arXiv preprint, 2021
Zusammenfassung
A plethora of dimensionality reduction techniques have emerged over the past decades, leaving researchers and analysts with a wide variety of choices for reducing their data, all the more so given some techniques come with additional parametrization (e.g. t-SNE, UMAP, etc.). Recent studies are showing that people often use dimensionality reduction as a black-box regardless of the specific properties the method itself preserves. Hence, evaluating and comparing 2D projections is usually qualitatively decided, by setting projections side-by-side and letting human judgment decide which projection is the best. In this work, we propose a quantitative way of evaluating projections, that nonetheless places human perception at the center. We run a comparative study, where we ask people to select 'good' and 'misleading' views between scatterplots of low-level projections of image datasets, simulating the way people usually select projections. We use the study data as labels for a set of quality metrics whose purpose is to discover and quantify what exactly people are looking for when deciding between projections. With this proxy for human judgments, we use it to rank projections on new datasets, explain why they are relevant, and quantify the degree of subjectivity in projections selected.BibTeX
Munz, Tanja ; Väth, Dirk ; Kuznecov, Paul ; Vu, Thang ; Weiskopf, Daniel: Visual-Interactive Neural Machine Translation. In: Graphics Interface 2021, Graphics Interface 2021, 2021
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Müller, Thomas ; Schulz, Christoph ; Weiskopf, Daniel: Adaptive Polygon Rendering for Interactive Visualization in the Schwarzschild Spacetime. In: European Journal of Physics, European Journal of Physics. Bd. 43, IOP Publishing (2021), Nr. 1, S. 015601
Zusammenfassung
Interactive visualization is a valuable tool for introductory or advanced courses in general relativity as well as for public outreach to provide a deeper understanding of the visual implications due to curved spacetime. In particular, the extreme case of a black hole where the curvature becomes so strong that even light cannot escape, benefits from an interactive visualization where students can investigate the distortion effects by moving objects around. However, the most commonly used technique of four-dimensional general-relativistic ray tracing is still too slow for interactive frame rates. Therefore, we propose an efficient and adaptive polygon rendering method that takes light deflection and light travel time into account. An additional advantage of this method is that it provides a natural demonstration of how multiple images occur and how light travel time affects them. Finally, we present our method using three example scenes: a triangle passing behind a black hole, a sphere orbiting a black hole and an accretion disk with different inclination angles.BibTeX
Pflüger, Hermann: A language to analyze, describe, and explore collections of visual art. In: Visual Computing for Industry, Biomedicine, and Art, Visual Computing for Industry, Biomedicine, and Art. Bd. 4, Springer Science and Business Media LLC (2021), Nr. 1
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Rau, Simeon ; Heyen, Frank ; Sedlmair, Michael: Visual Support for Human-AI Co-Composition. In: Extended Abstracts for the Late-Breaking Demo Session of the 22nd Int. Society for Music Information Retrieval Conf. (ISMIR), Extended Abstracts for the Late-Breaking Demo Session of the 22nd Int. Society for Music Information Retrieval Conf. (ISMIR) : ISMIR, 2021
Zusammenfassung
We propose a visual approach for AI-assisted music composition, where the user interactively generates, selects, and adapts short melodies. Based on an entered start melody, we automatically generate multiple continuation samples. Repeating this step and in turn generating continuations for these samples results in a tree or graph of melodies. We visualize this structure with two visualizations, where nodes display the piano roll of the corresponding sample. By interacting with these visualizations, the user can quickly listen to, choose, and adapt melodies, to iteratively create a composition. A third visualization provides an overview over larger numbers of samples, allowing for insights into the AI's predictions and the sample space.BibTeX
Rijken, Gerrit J ; Cutura, Rene ; Heyen, Frank ; Sedlmair, Michael ; Correll, Michael ; Dykes, Jason ; Smit, Noeska: Illegible Semantics: Exploring the Design Space of Metal Logos. In: IEEE VIS alt.VIS Workshop, IEEE VIS alt.VIS Workshop, 2021
Zusammenfassung
The logos of metal bands can be by turns gaudy, uncouth, or nearly illegible. Yet, these logos work: they communicate sophisticated notions of genre and emotional affect. In this paper we use the design considerations of metal logos to explore the space of "illegible semantics": the ways that text can communicate information at the cost of readability, which is not always the most important objective. In this work, drawing on formative visualization theory, professional design expertise, and empirical assessments of a corpus of metal band logos, we describe a design space of metal logos and present a tool through which logo characteristics can be explored through visualization. We investigate ways in which logo designers imbue their text with meaning and consider opportunities and implications for visualization more widely.BibTeX
Schatz, K. ; Müller, C. ; Gralka, P. ; Heinemann, M. ; Straub, A. ; Schulz, C. ; Braun, M. ; Rau, T. ; u. a.: 2019 IEEE Scientific Visualization Contest Winner: Visual Analysis of Structure Formation in Cosmic Evolution. In: IEEE Computer Graphics and Applications (CG&A), IEEE Computer Graphics and Applications (CG&A). Bd. 41 (2021), Nr. 06, S. 101–110
Zusammenfassung
Simulations of cosmic evolution are a means to explain the formation of the universe as we see it today. The resulting data of such simulations comprise numerous physical quantities, which turns their analysis into a complex task. Here, we analyze such high-dimensional and time-varying particle data using various visualization techniques from the fields of particle visualization, flow visualization, volume visualization, and information visualization. Our approach employs specialized filters to extract and highlight the development of so-called active galactic nuclei and filament structures formed by the particles. Additionally, we calculate X-ray emission of the evolving structures in a pre-processing step to complement visual analysis. Our approach is integrated into a single visual analytics framework to allow for analysis of star formation at interactive frame rates. Finally, we lay out the methodological aspects of our work that led to success at the 2019 IEEE SciVis Contest.BibTeX
Schatz, Karsten ; Franco Moreno, Juan José ; Schäfer, Marco ; Rose, Alexander S. ; Ferrario, Valerio ; Pleiss, Jürgen ; Vázquez, Pere-Pau ; Ertl, Thomas ; u. a.: Visual Analysis of Large-Scale Protein-Ligand Interaction Data. In: Computer Graphics Forum, Computer Graphics Forum. Bd. 40 (2021), Nr. 6, S. 394–408
Zusammenfassung
When studying protein-ligand interactions, many different factors can influence the behaviour of the protein as well as the ligands. Molecular visualisation tools typically concentrate on the movement of single ligand molecules; however, viewing only one molecule can merely provide a hint of the overall behaviour of the system. To tackle this issue, we do not focus on the visualisation of the local actions of individual ligand molecules but on the influence of a protein and their overall movement. Since the simulations required to study these problems can have millions of time steps, our presented system decouples visualisation and data preprocessing: our preprocessing pipeline aggregates the movement of ligand molecules relative to a receptor protein. For data analysis, we present a web-based visualisation application that combines multiple linked 2D and 3D views that display the previously calculated data The central view, a novel enhanced sequence diagram that shows the calculated values, is linked to a traditional surface visualisation of the protein. This results in an interactive visualisation that is independent of the size of the underlying data, since the memory footprint of the aggregated data for visualisation is constant and very low, even if the raw input consisted of several terabytes.BibTeX
Schatz, Karsten ; Frieß, Florian ; Schäfer, Marco ; Buchholz, Patrick C. F. ; Pleiss, Jürgen ; Ertl, Thomas ; Krone, Michael: Analyzing the similarity of protein domains by clustering Molecular Surface Maps. In: Computers & Graphics, Computers & Graphics. Bd. 99 (2021), S. 114–127
Zusammenfassung
Many biochemical and biomedical applications such as protein engineering or drug design are concerned with finding functionally similar proteins, however, this remains to be a challenging task. We present a new image-based approach for identifying and visually comparing proteins with similar function that builds on the hierarchical clustering of Molecular Surface Maps. Such maps are two-dimensional representations of complex molecular surfaces and can be used to visualize the topology and different physico-chemical properties of proteins. Our method is based on the idea that visually similar maps also imply a similarity in the function of the mapped proteins. To determine map similarity, we compute descriptive feature vectors using image moments, color moments, or a Convolutional Neural Network and use them for a hierarchical clustering of the maps. We demonstrate the feasibility of our approach using two data sets: an ensemble of hand-selected proteins with known similarities used for verification and an ensemble of ketolase enzymes, where we analyzed the individual domains using our method. Our method is integrated in an interactive visualization application, which allows users to explore and analyze the results. It visualizes the hierarchical clustering and offers linked views that provide details for a comparative data analysis.BibTeX
Schulz, Christoph ; Kwan, Kin Chung ; Becher, Michael ; Baumgartner, Daniel ; Reina, Guido ; Deussen, Oliver ; Weiskopf, Daniel: Multi-Class Inverted Stippling. In: ACM Trans. Graph., ACM Trans. Graph. Bd. 40. New York, NY, USA, Association for Computing Machinery (2021), Nr. 6
Zusammenfassung
We introduce inverted stippling, a method to mimic an inversion technique used by artists when performing stippling. To this end, we extend Linde-Buzo-Gray (LBG) stippling to multi-class LBG (MLBG) stippling with multiple layers. MLBG stippling couples the layers stochastically to optimize for per-layer and overall blue-noise properties. We propose a stipple-based filling method to generate solid color backgrounds for inverting areas. Our experiments demonstrate the effectiveness of MLBG in terms of reducing overlapping and intensity accuracy. In addition, we showcase MLBG with color stippling and dynamic multi-class blue-noise sampling, which is possible due to its support for temporal coherence.BibTeX
Straub, Alexander ; Karch, Grzegorz K. ; Sadlo, Filip ; Ertl, Thomas: Implicit Visualization of 2D Vector Field Topology for Periodic Orbit Detection. In: Hotz, I. ; Bin Masood, T. ; Sadlo, F. ; Tierny, J. (Hrsg.) ; Hotz, I. ; Bin Masood, T. ; Sadlo, F. ; Tierny, J. (Hrsg.): Topological Methods in Data Analysis and Visualization VI, Topological Methods in Data Analysis and Visualization VI : Springer International Publishing, 2021 — ISBN 978-3-030-83500-2, S. 159–180
Zusammenfassung
We present implicit visualization of 2D vector field topology, and show its utility for validating and guiding approaches for periodic orbit extraction. Instead of following the traditional approach by explicit extraction of the topological skeleton, we investigate its implicit visualization by approaches that label the regions that are separated by the skeleton. While such approaches perform well for gradient fields, they fail, in particular, to visualize periodic orbits. This motivates us to complement the label-based approach with a closely related distance-based metric. We show that our approach is able to reveal periodic orbits, also in configurations in which the state-of-the-art techniques for periodic orbit extraction fail, and demonstrate their utility for interactive extraction of all periodic orbits of a 2D vector field.BibTeX
Tkachev, Gleb ; Frey, Steffen ; Ertl, Thomas: S4: Self-Supervised learning of Spatiotemporal Similarity. In: IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics. (2021) — ISBN 10.1109/TVCG.2021.3101418
Zusammenfassung
We introduce an ML-driven approach that enables interactive example-based queries for similar behavior in ensembles of spatiotemporal scientific data. This addresses an important use case in the visual exploration of simulation and experimental data, where data is often large, unlabeled and has no meaningful similarity measures available. We exploit the fact that nearby locations often exhibit similar behavior and train a Siamese Neural Network in a self-supervised fashion, learning an expressive latent space for spatiotemporal behavior. This space can be used to find similar behavior with just a few user-provided examples. We evaluate this approach on several ensemble datasets and compare with multiple existing methods, showing both qualitative and quantitative results.BibTeX
Waldner, Manuela ; Geymayer, Thomas ; Schmalstieg, Dieter ; Sedlmair, Michael: Linking unstructured evidence to structured observations. In: Information Visualization, Information Visualization. Bd. 20 (2021), Nr. 1, S. 47--65
Zusammenfassung
Many professionals, like journalists, writers, or consultants, need to acquire information from various sources, make sense of this unstructured evidence, structure their observations, and finally create and deliver their product, such as a report or a presentation. In formative interviews, we found that tools allowing structuring of observations are often disconnected from the corresponding evidence. Therefore, we designed a sensemaking environment with a flexible observation graph that visually ties together evidence in unstructured documents with the user’s structured knowledge. This is achieved through bi-directional deep links between highlighted document portions and nodes in the observation graph. In a controlled study, we compared users’ sensemaking strategies using either the observation graph or a simple text editor on a large display. Results show that the observation graph represents a holistic, compact representation of users’ observations, which can be linked to unstructured evidence on demand. In contrast, users taking textual notes required much more display space to spatially organize source documents containing unstructured evidence. This implies that spatial organization is a powerful strategy to structure observations even if the available space is limited.BibTeX
Zhou, L. ; Johnson, C. R. ; Weiskopf, D.: Data-Driven Space-Filling Curves. In: IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Visualization and Computer Graphics. Bd. 27 (2021), Nr. 2, S. 1591–1600
Zusammenfassung
We propose a data-driven space-filling curve method for 2D and 3D visualization. Our flexible curve traverses the data elements in the spatial domain in a way that the resulting linearization better preserves features in space compared to existing methods. We achieve such data coherency by calculating a Hamiltonian path that approximately minimizes an objective function that describes the similarity of data values and location coherency in a neighborhood. Our extended variant even supports multiscale data via quadtrees and octrees. Our method is useful in many areas of visualization including multivariate or comparative visualization ensemble visualization of 2D and 3D data on regular grids or multiscale visual analysis of particle simulations. The effectiveness of our method is evaluated with numerical comparisons to existing techniques and through examples of ensemble and multivariate datasets.BibTeX