The Influence Explorer (video)—a tool for design
Conference Companion on Human Factors in Computing Systems
Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Design galleries: a general approach to setting parameters for computer graphics and animation
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Image graphs—a novel approach to visual data exploration
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
A spreadsheet interface for visualization exploration
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Outlier-Preserving Focus+Context Visualization in Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
A Grid-Inspired Mechanism for Coarse-Grained Experiment Execution
DS-RT '08 Proceedings of the 2008 12th IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications
Multiscale Time Activity Data Exploration via Temporal Clustering Visualization Spreadsheet
IEEE Transactions on Visualization and Computer Graphics
Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Result-Driven Exploration of Simulation Parameter Spaces for Visual Effects Design
IEEE Transactions on Visualization and Computer Graphics
SignalLens: Focus+Context Applied to Electronic Time Series
IEEE Transactions on Visualization and Computer Graphics
A Bayesian interactive optimization approach to procedural animation design
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Enhancing the Scalability of Simulations by Embracing Multiple Levels of Parallelization
PDMC-HIBI '10 Proceedings of the 2010 Ninth International Workshop on Parallel and Distributed Methods in Verification, and Second International Workshop on High Performance Computational Systems Biology
Visualization of Parameter Space for Image Analysis
IEEE Transactions on Visualization and Computer Graphics
Exploratory Analysis of Time-Series with ChronoLenses
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Multi-resolution techniques for visual exploration of large time-series data
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
Heterogeneity-based guidance for exploring multiscale data in systems biology
BIOVIS '12 Proceedings of the 2012 IEEE Symposium on Biological Data Visualization (BioVis)
A visual analytics approach for peak-preserving prediction of large seasonal time series
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Uncertainty-aware exploration of continuous parameter spaces using multivariate prediction
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Proceedings of the Winter Simulation Conference
Proceedings of the Winter Simulation Conference
Reversible simulations of elastic collisions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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The visualization of simulation trajectories is a well-established approach to analyze simulated processes. Likewise, the visualization of the parameter space that configures a simulation is a well-known method to get an overview of possible parameter combinations. This paper follows the premise that both of these approaches are actually two sides of the same coin; since the input parameters influence the simulation outcome, it is desirable to visualize and explore both in a combined manner. The main challenge posed by such an integrated visualization is the combinatorial explosion of possible parameter combinations. It leads to insurmountably high simulation runtimes and screen space requirements for their visualization. The Visual Analytics approach presented in this paper targets this issue by providing a visualization of a coarsely sampled subspace of the parameter space and its corresponding simulation outcome. In this visual representation, the analyst can identify regions for further drill-down and thus finer subsampling. We aid this identification by providing visual cues based on heterogeneity metrics. These indicate in which regions of the parameter space deviating behavior occurs at a more fine-grained scale and thus warrants further investigation and possible re-computation. We demonstrate our approach in the domain of systems biology by a visual analysis of a rule-based model of the canonical Wnt signaling pathway that plays a major role in embryonic development. In this case, the aim of the domain experts was to systematically explore the parameter space to determine those parameter configurations that match experimental data sufficiently well.