Scalable Visualization and Constrained Interaction for Large Graphs -- Supporting the Collaborative Analysis of High-dimensional Data Sets

在这个研究项目中，PI建议开发一种新的方法来可视化并与大型互联高维数据集交互，这些数据集表示为大型非结构化图。这种图中节点和边的底层语义要保持灵活，但最终目标是让分析人员从整体上理解数据世界，并使他或她能够发出和解决特定的数据查询。分析师还应该有一种简单的方法，告诉同事他们在与系统交互过程中收集到的见解，包括证据链和新的假设。

In this research project, the PI proposes to develop novel methodology to visualize and interact with large interconnected high-dimensional datasets represented as large unstructured graphs. The underlying semantics for the nodes and edges in such a graph are to be kept flexible, but the ultimate goal is for an analyst to acquire an understanding of the data universe as a whole, and to enable him or her to issue and resolve specific data queries. An analyst should also have an easy way to inform a colleague about the insights gathered during their own interaction with the system, including evidence chains and new hypotheses.