Modeling the Uncertainty Due to Data/Visual Transformations Using Sensitivity Analysis

在这个项目中，研究人员研究了视觉分析过程中将不确定度与灵敏度分析相结合的基本方面。他们还致力于开发新的和可伸缩的灵敏度的直观表示，从法律灵敏度系数的可视化到从分析获得的多变量导数的可视总结。具有不确定性意识的可视化分析有助于提高分析师对从分析中获得的见解的信心水平。此外，它还为工具制造商提供了测量和比较数据和视觉转换的稳健性的方法学。数据和可视化转换的灵敏度系数有助于发现影响输出可变性的主要因素，识别原始数据空间中不同转换的稳定区域，并告诉分析人员变量、输出和转换之间的相互作用。在大多数真实世界的应用程序中，不确定性被引入到数据生成、转换和分析的整个过程中。因此，将不确定性融入视觉分析的能力对于有洞察力的推理和关键决策至关重要。这个项目将对那些依赖于对大量数据进行推理的能力的领域产生广泛的影响。一方面，它建议提供视觉分析过程的变化视图，这为视觉数据分析和挖掘开辟了新的方向和范式。另一方面，对视觉分析过程的更好理解将有助于该领域成为一门科学学科。

In this project, the investigators study the fundamental aspects ofincorporating uncertainty with sensitivity analysis in the visualanalytics process. They also aim to develop novel and scalablevisual representations of sensitivity, from the visualization of theraw sensitivity coefficients to visual summaries of multivariatederivatives obtained from the analysis. Uncertainty-aware visualanalytics helps enhance analysts' confidence levels on the insightgained from the analysis. Furthermore, it gives toolmakers amethodology for measuring and comparing the robustness ofdata and visual transformations. Sensitivity coefficients of data andvisual transformations are useful for discovering the factors that mostlycontribute to output variability, identifying stability regions of thedifferent transformations within the original data space, andtelling the analyst what the interaction is between variables,outputs and transformations.Uncertainty is introduced throughout the process of data generation,transformation, and analysis in most real-world applications. The ability toincorporate uncertainty into visual analysis is therefore critically importantfor insightful reasoning and key decision making. This project will have awide-reaching impact on those areas relying on the ability to reasonabout large amounts of data. On one hand, it suggests to provide a variationalview of the visual analytics process, which opens up new directions andparadigms for visual data analysis and mining. On the other hand,the improved understanding of the visual analytics process will helpestablish the field as a scientific discipline.