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Interactive visual analysis of multi-faceted scientific data
- Dept. of Informatics, Univ. of
"... Abstract—Visualization and visual analysis play important roles in exploring, analyzing and presenting scientific data. In many disciplines, data and model scenarios are becoming multi-faceted: data are often spatio-temporal and multi-variate; they stem from different data sources (multi-modal data) ..."
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Cited by 25 (4 self)
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Abstract—Visualization and visual analysis play important roles in exploring, analyzing and presenting scientific data. In many disciplines, data and model scenarios are becoming multi-faceted: data are often spatio-temporal and multi-variate; they stem from different data sources (multi-modal data), from multiple simulation runs (multi-run/ensemble data), or from multi-physics simulations of interacting phenomena (multi-model data resulting from coupled simulation models). Also, data can be of different dimensionality or structured on various types of grids that need to be related or fused in the visualization. This heterogeneity of data characteristics presents new opportunities as well as technical challenges for visualization research. Visualization and interaction techniques are thus often combined with computational analysis. In this survey, we study existing methods for visualization and interactive visual analysis of multi-faceted scientific data. Based on a thorough literature review, a categorization of approaches is proposed. We cover a wide range of fields and discuss to which degree the different challenges are matched with existing solutions for visualization and visual analysis. This leads to conclusions with respect to promising research directions, for instance, to pursue new solutions for multi-run and multi-model data as well as techniques that support a multitude of facets. Index Terms—Visualization, interactive visual analysis, multi-run, multi-model, multi-modal, multi-variate, spatio-temporal data. 1
Tuner: Principled parameter finding for image segmentation algorithms using visual response surface exploration
- IEEE Transactions on Visualization and Computer Graphics
, 2011
"... Abstract—In this paper we address the difficult problem of parameter-finding in image segmentation. We replace a tedious manual process that is often based on guess-work and luck by a principled approach that systematically explores the parameter space. Our core idea is the following two-stage techn ..."
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Cited by 22 (6 self)
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Abstract—In this paper we address the difficult problem of parameter-finding in image segmentation. We replace a tedious manual process that is often based on guess-work and luck by a principled approach that systematically explores the parameter space. Our core idea is the following two-stage technique: We start with a sparse sampling of the parameter space and apply a statistical model to estimate the response of the segmentation algorithm. The statistical model incorporates a model of uncertainty of the estimation which we use in conjunction with the actual estimate in (visually) guiding the user towards areas that need refinement by placing additional sample points. In the second stage the user navigates through the parameter space in order to determine areas where the response value (goodness of segmentation) is high. In our exploration we rely on existing ground-truth images in order to evaluate the ”goodness ” of an image segmentation technique. We evaluate its usefulness by demonstrating this technique on two image segmentation algorithms: a three parameter model to detect microtubules in electron tomograms and an eight parameter model to identify functional regions in dynamic Positron Emission Tomography scans. Index Terms—Parameter exploration, Image segmentation, Gaussian Process Model. 1
Nodes on Ropes: A Comprehensive Data and Control Flow for Steering Ensemble Simulations
"... Abstract—Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive ..."
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Cited by 8 (3 self)
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Abstract—Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle several problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for uncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how these uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the simulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible at the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local knowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for input uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The meta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The meta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use the data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a domain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response strategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening
Design by dragging: An interface for creative forward and inverse design with simulation ensembles
- IEEE Trans. Vis. Comput. Graph
"... Fig. 1: In Design by Dragging, designers navigate through a space of hundreds of simulation outputs using direct manipulation interfaces on top of data visualizations. In this example, medical device engineers refine the design of a mechanical biopsy device with two concentric cylinders (cannulas) t ..."
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Cited by 8 (2 self)
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Fig. 1: In Design by Dragging, designers navigate through a space of hundreds of simulation outputs using direct manipulation interfaces on top of data visualizations. In this example, medical device engineers refine the design of a mechanical biopsy device with two concentric cylinders (cannulas) that slide against each other to cut tissue. In forward design (left), drag operations change the value of simulation inputs, such as the length of the cutting window. In inverse design (right), drag operations directly change the simulation outputs. Users bend and reshape stress fields and the system responds continuously, displaying morphs between the pre-computed simulation results. Abstract—We present an interface for exploring large design spaces as encountered in simulation-based engineering, design of visual effects, and other tasks that require tuning parameters of computationally-intensive simulations and visually evaluating results. The goal is to enable a style of design with simulations that feels as-direct-as-possible so users can concentrate on creative design tasks. The approach integrates forward design via direct manipulation of simulation inputs (e.g., geometric properties, applied forces) in the same visual space with inverse design via “tugging ” and reshaping simulation outputs (e.g., scalar fields from finite element analysis (FEA) or computational fluid dynamics (CFD)). The interface includes algorithms for interpreting the intent of users ’ drag operations relative to parameterized models, morphing arbitrary scalar fields output from FEA and CFD simulations, and in-place interactive ensemble visualization. The inverse design strategy can be extended to use multi-touch input in combination with an as-rigid-as-possible shape manipulation to support rich visual queries. The potential of this new design approach is confirmed via two applications: medical device engineering of a vacuum-assisted biopsy device and visual effects design using a physically based flame simulation. Index Terms—design, simulation, direct manipulation, multi-touch 1
Transgraph: Hierarchical exploration of transition relationships in time-varying volumetric data
- IEEE Transactions on Visualization and Computer Graphics
"... Fig. 1. Left: the TransGraph of the earthquake data set with dynamic tracking. We select a volume region corresponding to the earthquake’s epicenter at time step 34, which is highlighted in its original color saturation in (a). Right: (a) to (f) are the dynamic ..."
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Cited by 6 (1 self)
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Fig. 1. Left: the TransGraph of the earthquake data set with dynamic tracking. We select a volume region corresponding to the earthquake’s epicenter at time step 34, which is highlighted in its original color saturation in (a). Right: (a) to (f) are the dynamic
VAICo: Visual analysis for image comparison
- IEEE Trans. Vis. Comput. Graph
"... Accepted for publication by IEEE. ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/ ..."
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Cited by 5 (3 self)
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Accepted for publication by IEEE. ©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/
Visual parameter space analysis: A conceptual framework
- IEEE TVCG (Proc. InfoVis
"... Abstract—Various case studies in different application domains have shown the great potential of visual parameter space analysis to support validating and using simulation models. In order to guide and systematize research endeavors in this area, we provide a conceptual framework for visual paramete ..."
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Cited by 3 (0 self)
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Abstract—Various case studies in different application domains have shown the great potential of visual parameter space analysis to support validating and using simulation models. In order to guide and systematize research endeavors in this area, we provide a conceptual framework for visual parameter space analysis problems. The framework is based on our own experience and a structured analysis of the visualization literature. It contains three major components: (1) a data flow model that helps to abstractly describe visual parameter space analysis problems independent of their application domain; (2) a set of four navigation strategies of how parameter space analysis can be supported by visualization tools; and (3) a characterization of six analysis tasks. Based on our framework, we analyze and classify the current body of literature, and identify three open research gaps in visual parameter space analysis. The framework and its discussion are meant to support visualization designers and researchers in characterizing parameter space analysis problems and to guide their design and evaluation processes. Index Terms—Parameter space analysis, input-output model, simulation, task characterization, literature analysis. 1
AM. Interactive visual exploration of simulator accuracy: A case study for stochastic simulation algorithms
- In: Proceedings of WSC’12. IEEE Press; 2012
"... Visual Analytics offers various interesting methods to explore high dimensional data interactively. In this paper we investigate how it can be applied to support experimenters and developers of simulation software conducting simulation studies. In particular the usage and development of approximate ..."
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Cited by 2 (1 self)
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Visual Analytics offers various interesting methods to explore high dimensional data interactively. In this paper we investigate how it can be applied to support experimenters and developers of simulation software conducting simulation studies. In particular the usage and development of approximate simulation algorithms poses several practical problems, e.g., estimating the impact of algorithm parameters on accuracy or detecting faulty implementations. To address some of those problems, we present an approach that allows to relate configurations and accuracy visually and exploratory. The approach is evaluated by a brief case study, focusing on the accuracy of Stochastic Simulation Algorithms. 1
Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles
"... Fig. 1. An ensemble of a 2D convection flow field is analyzed using the proposed joint variance visualization techniques. From left to right: Individual variances of four of the data set runs show high variances around the heating cylinder. Brushing in the classification space allows for the identif ..."
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Cited by 1 (0 self)
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Fig. 1. An ensemble of a 2D convection flow field is analyzed using the proposed joint variance visualization techniques. From left to right: Individual variances of four of the data set runs show high variances around the heating cylinder. Brushing in the classification space allows for the identification of similar (green), dissimilar (red), and uncertain regions (blue and white). Together with a color mapped visualization of the ensemble domain and interactive pathline seeding, a complete analysis of transport is possible. Abstract—Sets of simulation runs based on parameter and model variation, so-called ensembles, are increasingly used to model physical behaviors whose parameter space is too large or complex to be explored automatically. Visualization plays a key role in conveying important properties in ensembles, such as the degree to which members of the ensemble agree or disagree in their output. For ensembles of time-varying vector fields, there are numerous challenges for providing an expressive comparative visualization, among which is the requirement to relate the effect of individual flow divergence to joint transport characteristics of the ensemble. Yet, techniques developed for scalar ensembles are of little use in this context, as the notion of transport induced by a vector field cannot be modeled using such tools. We develop a Lagrangian framework for the comparison of flow fields in an ensemble. Our techniques evaluate individual and joint transport variance and introduce a classification space that facilitates incorporation of these properties into a common ensemble visualization. Variances of Lagrangian neighborhoods are computed using pathline integration and Principal Components Analysis. This allows for an inclusion of uncertainty measurements into the visualization and analysis approach. Our results demonstrate the usefulness and expressiveness of the presented method on several practical examples.
Mixing Board Versus Mouse Interaction In Value Adjustment Tasks
, 2011
"... We present a controlled, quantitative study with 12 participants comparing interaction with a haptically enhanced mixing board against interaction with a mouse in an abstract task that is motivated by several practical parameter space exploration settings. The study participants received 24 sets of ..."
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Cited by 1 (1 self)
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We present a controlled, quantitative study with 12 participants comparing interaction with a haptically enhanced mixing board against interaction with a mouse in an abstract task that is motivated by several practical parameter space exploration settings. The study participants received 24 sets of one to eight integer values between 0 and 127, which they had to match by making adjustments with physical or graphical sliders, starting from a default position of 64. Based on recorded slider motion path data, we developed an analysis algorithm that identifies and measures different types of activity intervals, including error time moving irrelevant sliders and end time in breaks after completing each trial item. This decomposition facilitates data cleaning and more selective outlier removal, which is adequate for the small sample size. Our results showed a significant increase in speed of the mixing board interaction accompanied by reduced perceived cognitive load when compared with the traditional mouse-based GUI interaction. We noticed that the gains in speed are largely due to the improved times required for the hand to reach for the first slider (acquisition time) and also when moving between different ones, while the actual time spent manipulating task-relevant sliders is very similar for either input device. These results agree strongly with qualitative predictions from Fitts ’ Law that the larger targets afforded by the mixer handles contributed to its faster performance. Our study confirmed that the advantage of the mixing board acquisition times and between times increases, as more sliders need to be manipulated in parallel. To investigate this further, we computed a measure of motion simultaneity based on velocity
