Advanced Quality Metrics in Information Visualization and Scientific Visualization

信息可视化和科学可视化中的高级质量指标

• 批准号: 274337765
• 负责人: Professor Dr.-Ing. Dirk Joachim Lehmann
• 金额: --
• 依托单位: Institut für Simulation und Graphik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/274337765?language=en
• 关键词: Advanced; Quality; Metrics; Information; Visualization

Quality metrics are a promising concept for the automatic analysis of visualizations from high-dimensional data. In order to completely visualize a high-dimensional data set, a large number of visualizations are required. Just a subset of them shows relevant structures of the data and thus just a subset of them is required to be seen by the user. The idea of quality metrics is to automatically detect this subset of good visualizations. For this, they mimic the visual perception system. A couple of quality metrics are known aiming mostly at the analysis of bi-variate discrete visualizations of high-dimensional data. This project extends the traditional approach of quality metrics in three ways. The concept of quality metrics will be extended to nonlinear embeddings in multivariate projections, it will be extended to non-discrete visualizations (aka continuous visualizations), and it will be extended in order to measure the reliability of quality metrics. As the conceptional extensions are mutually related, we propose their treatment within one project.

对于高维数据的可视化自动分析，质量度量是一个很有前途的概念。为了完全可视化高维数据集，需要进行大量的可视化。其中只有一部分显示了数据的相关结构，因此用户只需要看到其中的一部分。质量度量的思想是自动检测良好可视化的这个子集。为此，它们模仿视觉感知系统。已知的几个质量度量主要针对高维数据的双变量离散可视化分析。该项目在三个方面扩展了传统的质量度量方法。质量度量的概念将被扩展到多元投影中的非线性嵌入，它将被扩展到非离散可视化(又名连续可视化)，并且它将被扩展以度量质量度量的可靠性。由于概念扩展是相互关联的，我们建议在一个项目中处理它们。

项目成果

The LloydRelaxer: An Approach to Minimize Scaling Effects for Multivariate Projections

LloydRelaxer：一种最小化多元投影尺度效应的方法

• DOI: 10.1109/tvcg.2017.2705189
• 发表时间: 2017
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Dirk J. Lehmann;Holger Theisel
• 通讯作者: Holger Theisel

Visual Exploration of Global Trade Networks with Time‐Dependent and Weighted Hierarchical Edge Bundles on GPU

GPU 上具有时间依赖性和加权分层边束的全球贸易网络的可视化探索

• DOI: 10.1111/cgf.13186
• 发表时间: 2017
• 期刊: Computer Graphics Forum
• 影响因子: 2.5
• 作者: Johannes Hofmann;Michael Groessler;Peter-Paul Pichler;Dirk J. Lehmann
• 通讯作者: Dirk J. Lehmann

Adaptable Radial Axes Plots for Improved Multivariate Data Visualization

• DOI: 10.1111/cgf.13196
• 发表时间: 2017-06
• 期刊: Computer Graphics Forum
• 影响因子: 2.5
• 作者: M. Rubio-Sánchez;Alberto Sánchez;D. Lehmann

Interactive Visual Exploration of Local Patterns in Large Scatterplot Spaces

• DOI: 10.1111/cgf.13404
• 发表时间: 2018-06
• 期刊: Computer Graphics Forum
• 影响因子: 2.5
• 作者: Mohammad Chegini;Lin Shao;Robert Gregor;D. Lehmann;K. Andrews;Tobias Schreck

Insight Beyond Numbers: The Impact of Qualitative Factors on Visual Data Analysis

超越数字的洞察：定性因素对可视化数据分析的影响

• DOI: 10.1109/tvcg.2020.3030376
• 发表时间: 2020
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Benjamin Karer;Hans Hagen;D. J. Lehmann
• 通讯作者: D. J. Lehmann