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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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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
Interactive Progressive Visualization with Space-Time Error Control
"... Abstract—We present a novel scheme for progressive rendering in interactive visualization. Static settings with respect to a certain image quality or frame rate are inherently incapable of delivering both high frame rate for rapid changes and high image quality for detailed investigation. Our techni ..."
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Abstract—We present a novel scheme for progressive rendering in interactive visualization. Static settings with respect to a certain image quality or frame rate are inherently incapable of delivering both high frame rate for rapid changes and high image quality for detailed investigation. Our technique flexibly adapts by steering the visualization process in three major degrees of freedom: when to terminate the refinement of a frame in the background and start a new one, when to display a frame currently computed, and how much resources to consume. We base these decisions on the correlation of the errors due to insufficient sampling and response delay, which we estimate separately using fast yet expressive heuristics. To automate the configuration of the steering behavior, we employ offline video quality analysis. We provide an efficient implementation of our scheme for the application of volume raycasting, featuring integrated GPU-accelerated image reconstruction and error estimation. Our implementation performs an integral handling of the changes due to camera transforms, transfer function adaptations, as well as the progression of the data to in time. Finally, the overall technique is evaluated with an expert study. Index Terms—Progressive visualization, error-based frame control, interactive volume raycasting. 1
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TVCG.2014.2346321, IEEE Transactions on Visualization and Com
"... 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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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
Evaluation: Thinking Outside the (Search) Box
"... Evaluation of IR systems has typically focused on the sys-tem and specifically assessing the quality of a ranked list of results with respect to a query. However, IR functionality is typically just one component amongst many that are used to help support users ’ wider information seeking activities. ..."
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Evaluation of IR systems has typically focused on the sys-tem and specifically assessing the quality of a ranked list of results with respect to a query. However, IR functionality is typically just one component amongst many that are used to help support users ’ wider information seeking activities. Many systems that include a search box also provide fea-tures, such as faceted lists, subject hierarchies, visualizations and recommendations to help users find information. In this paper I discuss experiences gained from developing a system to support exploration and discovery in digital cultural her-itage. In particular I focus on the development of system components to support search and navigation and how the different components were evaluated within the development life-cycle of the project. The importance of taking a holistic approach to evaluation, as well as utilising evaluation ap-proaches from domains other than IR, is emphasized. In short, we need to be thinking outside the (search) box when it comes to evaluation in IR. CCS Concepts •Information systems → Evaluation of retrieval re-sults; Retrieval effectiveness;
Towards an Understanding of Mobile Touch Navigation in a Stereoscopic Viewing Environment for 3D Data Exploration
"... Abstract—We discuss touch-based navigation of 3D visualizations in a combined monoscopic and stereoscopic viewing environment. We identify a set of interaction modes, and a workflow that helps users transition between these modes to improve their interaction experience. In our discussion we analyze, ..."
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Abstract—We discuss touch-based navigation of 3D visualizations in a combined monoscopic and stereoscopic viewing environment. We identify a set of interaction modes, and a workflow that helps users transition between these modes to improve their interaction experience. In our discussion we analyze, in particular, the control-display space mapping between the different reference frames of the stereoscopic and monoscopic displays. We show how this mapping supports interactive data exploration, but may also lead to conflicts between the stereoscopic and monoscopic views due to users ’ movement in space; we resolve these problems through synchronization. To support our discussion, we present results from an exploratory observational evaluation with domain experts in fluid mechanics and structural biology. These experts explored domain-specific datasets using variations of a system that embodies the interaction modes and workflows; we report on their interactions and qualitative feedback on the system and its workflow. Index Terms—Visualization of 3D data, human-computer interaction, expert interaction, direct-touch input, mobile displays, stereoscopic environments, VR, AR, conceptual model of interaction, interaction reference frame mapping, observational study. F 1
Visualization Evaluation for Cyber Security: Trends and Future Directions
"... The Visualization for Cyber Security research community (VizSec) addresses longstanding challenges in cyber security by adapting and evaluating information visualization tech-niques with application to the cyber security domain. This research e↵ort has created many tools and techniques that could be ..."
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The Visualization for Cyber Security research community (VizSec) addresses longstanding challenges in cyber security by adapting and evaluating information visualization tech-niques with application to the cyber security domain. This research e↵ort has created many tools and techniques that could be applied to improve cyber security, yet the commu-nity has not yet established unified standards for evaluating these approaches to predict their operational validity. In this paper, we survey and categorize the evaluation metrics, components and techniques that have been utilized in the past decade of VizSec research literature. We also discuss existing methodological gaps in evaluating visualization in cyber security, and suggest potential avenues for future re-search in order to help establish an agenda for advancing the state-of-the-art in evaluating cyber security visualization.
for more information. Curve Boxplot: Generalization of Boxplot for Ensembles of Curves
"... and a curve boxplot visualization of an ensemble of 50 simulated hurricane tracks (right). Abstract — In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Throug ..."
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and a curve boxplot visualization of an ensemble of 50 simulated hurricane tracks (right). Abstract — In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.
Navigating Reductionism and Holism in Evaluation
"... In this position paper, we enumerate two approaches to the evaluation of visualizations which are associated with two approaches to knowledge formation in science: reductionism, which holds that the understanding of complex phenomena is based on the understanding of simpler components; and holism, w ..."
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In this position paper, we enumerate two approaches to the evaluation of visualizations which are associated with two approaches to knowledge formation in science: reductionism, which holds that the understanding of complex phenomena is based on the understanding of simpler components; and holism, which states that complex phenomena have charac-teristics more than the sum of their parts and must be under-stood as complete, irreducible units. While we believe that each approach has benefits for evaluating visualizations, we claim that strict adherence to one perspective or the other can make it difficult to generate a full evaluative picture of visualization tools and techniques. We argue for move-ment between and among these perspectives in order to gen-erate knowledge that is both grounded (i.e. its constituent parts work) and validated (i.e. the whole operates correctly). We conclude with examples of techniques which we believe represent movements of this sort from our own work, high-lighting areas where we have both “built up ” reductionist techniques into larger contexts, and “broken down ” holistic techniques to create generalizable knowledge. 1.
To appear in IEEE Transactions on Visualization and Computer Graphics Design Activity Framework for Visualization Design
"... Abstract — An important aspect in visualization design is the connection between what a designer does and the decisions the designer makes. Existing design process models, however, do not explicitly link back to models for visualization design decisions. We bridge this gap by introducing the design ..."
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Abstract — An important aspect in visualization design is the connection between what a designer does and the decisions the designer makes. Existing design process models, however, do not explicitly link back to models for visualization design decisions. We bridge this gap by introducing the design activity framework, a process model that explicitly connects to the nested model, a well-known visualization design decision model. The framework includes four overlapping activities that characterize the design process, with each activity explicating outcomes related to the nested model. Additionally, we describe and characterize a list of exemplar methods and how they overlap among these activities. The design activity framework is the result of reflective discussions from a collaboration on a visualization redesign project, the details of which we describe to ground the framework in a real-world design process. Lastly, from this redesign project we provide several research outcomes in the domain of cybersecurity, including an extended data abstraction and rich opportunities for future visualization research.