CRII: SCH: Multidimensional Tree Diagram Visualization for Linked Data Exploration

树状图的分析和可视探索在成像科学(例如放射学、生物学、天文学等)中尤其具有挑战性。因为理想情况下，树状图需要在原始数据的上下文中进行查看和探索。从中导出树的原始数据可以由成像数据立方体(3D体积)、2D图像和定量(表格)数据的组合组成。用于这种相关数据集的可视探索的一种有用技术是链接视图，其中在每个单独的可视化中视觉地突出显示等价的数据。拟议研究项目的目标是开发树形图所需的新技术、方法和分类，以实现有效的交互式可视化数据探索，包括在多维关联数据的上下文中。这项提案的贡献适用于许多领域，包括医疗保健和医疗保健以外的领域。作为这项研究的一部分开发的新工具和分类法，以及教程和教学大纲，将通过会议和研讨会免费提供和分享。本提案中提出的研究将通过创建树形图的新技术、方法论和分类法来促进可视化的最新水平。这项研究的结果将能够以一种新颖和系统的方法，根据所需的分析任务，在多维环境中有效地设计交互式树形图。整个项目从分类抽象到可视化和编辑技术和方法，再到一个具有评估案例研究和用户测试的已实现系统，为可视化研究提供了一种模型方法。作为拟议工作的一部分，以下研究问题将被解决：(1)如何根据数据类型和分析任务选择最佳的树形图类型？以及(2)与树形图交互的最佳方法是什么，包括如何选择数据？为了回答这些问题，将创建一个新的树形图分类，以考虑数据类型、数据维度、量化数据编码选项和任务等概念。为了能够开发带有树形图的链接视图，将创建一个新的树形图任务分类，其中包括树形图的数据选择方法。树形图的分类和相关方法将被实施为交互式公共可用的工具，使用户能够为他们的数据和任务集选择或发明最合适的树形图，然后在用于可视化和分析多维数据集的链接视图数据可视化和探索环境中与其交互。为了评估新的分类和方法以及结合这些概念的新工具的可用性，将在脑成像的医疗保健领域进行真实世界的案例研究和可用性评估，目的是研究和开发一种新的脑血管树形图表示法。

The analysis and visual exploration of tree diagrams, visual representations of hierarchical data, is particularly challenging in the imaging sciences (e.g., radiology, biology, astronomy, etc.) as the tree diagrams ideally need to be viewed and explored within the context of the original data. The original data from which the tree was derived may be composed of a combination of imaging data cubes (3D volumes), 2D images, and quantitative (tabular) data. A useful technique for the visual exploration of such related data sets is linked views in which equivalent data is visually highlighted in each individual visualization. The goal of the proposed research project is to develop the novel techniques, methods, and taxonomies needed for tree diagrams to enable effective interactive visual data exploration including in the context of multidimensional linked data. The contributions of this proposal are applicable to many domains including and beyond healthcare. The new tools and taxonomies developed as part of this research, along with tutorials and syllabi, will be made freely available and shared through conferences and workshops.The research presented in this proposal will advance the state of the art in visualization through the creation of new techniques, methodologies, and taxonomies for tree diagrams. The results of the research will enable the effective design of interactive tree diagrams in a multidimensional context based on the required analytic tasks in a novel and systematic approach. The full project from taxonomy abstractions to visualization and editing techniques and methodologies to an implemented system with an evaluation case study and user testing provides a model approach to visualization research. The following research questions will be addressed as part of the proposed work: (1) How does one pick the optimal tree diagram type based on data type and analytic task? and (2) What are the best methods for interacting with tree diagrams including how to select data? To answer these questions a new taxonomy for tree diagrams will be created in order to take into account the concepts of data type, data dimensionality, quantitative data encoding options, and task. In order to enable the ability to develop linked views with tree diagrams, a new task taxonomy for tree diagrams will be created including data selection methods for tree diagrams. The taxonomies and related methodologies for tree diagrams will be implemented into an interactive publicly available tool enabling a user to select or invent the most appropriate tree diagram for their data and set of tasks, and then interact with it in a linked-view data visualization and exploration environment for visualizing and analyzing multidimensional datasets. In order to evaluate the new taxonomies and methodologies as well as the usability of the new tool incorporating these concepts, a real world case study and usability evaluation will be conducted in the healthcare field of brain imaging with the goal of investigating and developing a novel tree diagram representation of brain blood vessels.