Feng David, Lee Yueh, Kwock Lester, Taylor Russell M
UNC Computer Science.
Proc APGV. 2009;2009:61-68. doi: 10.1145/1620993.1621006.
We present a user study quantifying the effectiveness of Scaled Data-Driven Spheres (SDDS), a multivariate three-dimensional data set visualization technique. The user study compares SDDS, which uses separate sets of colored sphere glyphs to depict variable values, to superquadric glyphs, an alternative technique that maps all variable values to a single glyph. User study participants performed tasks designed to measure their ability to estimate values of particular variables and identify relationships among variables. Results from the study show that users were significantly more accurate and faster for both tasks under the SDDS condition.
我们展示了一项用户研究,该研究对缩放数据驱动球体(SDDS)这一多变量三维数据集可视化技术的有效性进行了量化。该用户研究将使用不同颜色球体符号集来描绘变量值的SDDS与超二次曲面符号(一种将所有变量值映射到单个符号的替代技术)进行了比较。用户研究的参与者执行了旨在测量他们估计特定变量值和识别变量之间关系能力的任务。研究结果表明,在SDDS条件下,用户在这两项任务上的准确性和速度都显著更高。