Visualizing User Interactions with Simulation Tools

In order to improve user experiences with simulation tools hosted by cyberinfrastructure, we endeavor to gain a better understanding of how users interact with tools. The dimensionality of these tools is often too large to be intuitively understood. This paper presents two contributions to the study of user behavior: the MEANDER algorithmfor visualizing sessions of user activity, and a scoring method ("searchiness") for characterizing a user's behavior along an axis of ``wildcatting'' vs. searching. The MEANDER algorithm uses graph heuristics to squash a high dimensional path of exploration into a (distorted) plane for rendering. The "searchiness'" score is built upon the same graph techniques.<br>

为提升用户在网络基础设施（cyberinfrastructure）托管的模拟工具上的使用体验，我们致力于更深入地理解用户与各类工具的交互模式。此类工具的维度往往过于庞大，难以通过直观方式进行把握。本研究对用户行为领域的探索做出两项贡献：其一为可可视化用户活动会话的MEANDER算法，其二为一种用于沿着「盲目探索」与「精准搜索」的维度刻画用户行为特征的评分方法（命名为"searchiness"）。MEANDER算法借助图启发式方法，将高维探索路径压缩至（存在畸变的）平面以实现可视化渲染。该"searchiness"评分方法同样基于上述图论技术构建。