本项目研究动机来自于大规模、高维数据可视化与交互技术的迫切需求，研究对象是大规模、高维点云数据，例如，自然科学领域的天文学星系粒子，生物学蜂群、鸟群和鱼群，社会人与事件之间的关系和发展等。这类大规模点云数据具有一个共同的特点，虽然它们是分布在三维空间中的非结构化粒子群，但其存在和分布都具有某种原因，若能通过某种简洁的方式表现其结构和隐含信息将会有效地帮助科学家理解和思考。本项目的研究内容即关于体现大规模，高维点云粒子空间的深度关系、三维拓扑结构和高维属性子空间的抽象表达的可视化方法，并在此基础上，提出有效的交互技术，帮助用户分析数据。我们期望通过可视化的方法帮助人们在观察复杂的数据时，始终保持对数据的空间意识和结构意识，即使，这个复杂的数据环境是一个包含数以千万、非结构化的点云粒子的空间。我们的最终目标是，使用户与这类大规模、高维的点云数据的交互，变得像与二维数据交互一样简单。

The motivation behind the proposed research program is the pressing need to visualize and interact with massive high-dimensional datasets (often referred to as Big Data) that have spatial components, that is, positions in three-dimensional space. Such data includes particle simulations in physics, astronomy, swarm behavior, molecular models in biology, chemistry, or material sciences. The predominantly spatial character of such “Big Data” implies that they cannot be treated as abstract data having arbitrary representations imposed on them. Instead, it is important that the spatial relations are preserved. .The project focuses on the most fundamental visualization and interaction techniques: navigation, selection, and representation. The main idea I plan to exploit in all of these cases is that data have structure that can be used to augment traditional techniques. This structure can be automatically determined and then used to facilitate different types of interaction or presented to the user in a simplified way. Furthermore, the project is structured so that collaboration with scientists that have specific visualization and interaction needs (astronomers and medical doctors) forms an integral part of it. The final aim of the project is to produce novel structure-aware visualization and interaction techniques for spatially-oriented data and integrate such methods with software tools already used by scientists in their specific domain. My vision is to finally make working with such spatially-oriented high-dimensional data, as easy and intuitive as working with two-dimensional data.