CAREER: Design Decision Patterns for Visualizing Multivariate Graphs

职业：设计可视化多元图的决策模式

• 批准号: 1350896
• 负责人: Miriah Meyer
• 金额: $ 50万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1350896&HistoricalAwards=false
• 关键词: CAREER; Design; Decision; Patterns; Visualizing

Multivariate graphs, or datasets that link together entities that are associated with multiple different variables, occur in a broad range of problems. For example, the dataset could be geospatial locations that include socio-economic statistics, linked together through a public transportation system. These multivariate graphs are notoriously difficult to visualize because the number of data variables exceeds the number of available visual cues - these cues include color, size, position, etc. The goal of this project is to establish a set of validated and generalizable techniques for visualizing and interacting with multivariate graphs. Three target application areas will drive the investigations: one in cancer biology, a second in urban transportation, and a third in particle physics. These areas were chosen to represent a wide spectrum of possible applications in which multivariate graphs play a central role, thus fostering generalizable results. The multidisciplinary nature of the research and the close collaboration with domain experts in our target application areas will provide a unique educational environment for undergraduate and graduate students, while also broadening the participation in computer science beyond traditional boundaries.This is the first systematic, problem-driven effort to consider the visualization of multivariate graphs using a diverse set of application areas, with the goal of developing a generalizable set of techniques and principles for supporting a broad range of visualization and data analysis tasks. The research will be conducted with domain experts using a design study methodology, which is a deeply collaborative and user-centered approach to visualization research. The primary impact of this work will be validated visualization design decision patterns for effective visual representation and user-driven exploration of complex multivariate graphs, resulting in a more comprehensive foundation of techniques for visualizing this increasingly important data type. The resulting design decision patterns will support ongoing research and discovery in our target application areas, as well generalize to a broad class of real-world problems. Furthermore, these patterns will form the foundation of software tools for visualizing multivariate graphs that effectively support exploration and sense-making of these complex data types by taking into account the varied relationships embedded within. Results and software will be disseminated to both the research communities of our target application areas, but also more broadly through the project website at http://mvgraphs.sci.utah.edu.

多元图或将与多个不同变量关联的实体链接在一起的多元图或数据集发生在广泛的问题中。例如，数据集可能是通过公共交通系统将社会经济统计的地理空间位置。众所周知，这些多元图很难可视化，因为数据变量的数量超过了可用的视觉提示数 - 这些提示包括颜色，大小，位置等。该项目的目标是建立一组经过验证且可概括的技术，以可视化和与多变量图进行可视化和交互。三个目标应用领域将推动研究：一种是癌症生物学，第二个城市运输，三分之一。选择这些区域以代表各种可能的应用，其中多元图起着核心作用，从而促进了可概括的结果。研究的多学科性质以及与我们目标应用领域中的领域专家的密切合作将为本科和研究生提供独特的教育环境，同时还扩大了计算机科学的参与，超出了传统界限以外的计算机科学。这是第一个系统的，问题驱动的努力，以实现多个瞄准范围的范围，以实现范围的范围，以范围的范围进行构图，该范围是在范围内开发的范围，该范围是范围内的范围，这些范围的范围是范围内的，范围的范围是一系列技术，这些范围是构成一般的应用程序，该范围是一套通用的技术，该范围是一般化的技术，该范围是一般化的一般范围，该范围是一般化的一般技术，和数据分析任务。这项研究将使用设计研究方法与领域专家进行，这是一种以用户为中心的可视化研究方法。这项工作的主要影响将得到验证的可视化设计决策模式，以进行有效的视觉表示和对复杂多元图的用户驱动探索，从而为可视化这种日益重要的数据类型的技术提供了更全面的基础。由此产生的设计决策模式将支持我们目标应用领域正在进行的研究和发现，并推广到一系列现实世界中的问题。此外，这些模式将构成软件工具的基础，用于可视化多元图，这些图形通过考虑到其中嵌入的各种关系，从而有效地支持这些复杂数据类型的探索和感知。结果和软件将被传播到我们目标应用领域的两个研究社区，但也将通过项目网站http://mvgraphs.sci.utah.edu更广泛地传播。