SPP 1335: Scalable Visual Analytics: Interactive Visual Analysis Systems of Complex Information Spaces

在研究和开发以及许多应用领域中产生了复杂性和动态性迅速增长的数据集。一个主要的挑战是发现重要的信息，并以适当的方式将其传达给人类。交互式可视化数据分析技术通过自动数据分析技术扩展了人类的感知和认知能力。只有结合数据分析和可视化技术，才能有效地访问难以管理的复杂数据集。可视化分析技术使意外更容易被发现，并有助于获得新的见解。可视化分析领域的主要目标是用图形化的方式表示真实或抽象的数据，这样可以很容易地检测到数据的结构连接、相关特征和其他有趣的属性。优先项目的重点是研究新的视觉分析算法的理论基础，可扩展的视觉分析技术的开发和实际实施，以及它们的集成和评估。一个核心挑战是可扩展性，它不仅涉及数据集的大小，还涉及数据的重要属性，如维度、生产率、同质性、现实性、精度和完整性。此外，可视化分析技术本身应该是可扩展的，这意味着它们应该是交互式的，并传达数据的质量和相关性。可视化分析方法的可扩展性只能通过计算机科学不同领域的科学家之间的密切合作来实现。优先计划的参加者来自可视化、数据分析和数据库技术以及人机交互等研究领域，但也包括其他有助于视觉分析的领域，如统计分析、地理数据分析和认知科学。大多数项目结合了至少两个不同的研究领域。目标是开发新技术，这些技术成功地应用于具体应用，并比现有方法有重大改进。

Data sets with rapidly growing complexity and dynamics are generated in research and development as well as in numerous application areas. A central challenge is to detect the important information and to communicate it to humans in an appropriate way. Interactive visual data analysis techniques extend the perceptual and cognitive abilities of humans with automatic data analysis techniques. Only by a combination of data analysis and visualisation techniques, an effective access to otherwise unmanageably complex data sets is possible. Visual analysis techniques make the unexpected more easily discoverable and help to gain new insights. The primary goal in the field of visual analytics is to represent real or abstract data graphically in a way that structural connections, relevant characteristics and other interesting properties of the data can be easily detected. Focus of the Priority Programme is research covering the theoretical foundations of new visual analytics algorithms, the development and practical implementation of scalable visual analytics techniques, as well as their integration and evaluation. A central challenge is scalability, which relates not only to the size of the data set but also to important properties of the data such as dimensionality, production rate, homogeneity, actuality, precision and completeness. In addition, the visual analytics techniques themselves should be scalable, which means that they should be interactive and convey the quality and relevance of the data. The scalability of visual analytics methods can only be achieved by a close cooperation between scientists from different areas of computer science. Participants in the Priority Programme come from the research areas visualisation, data analysis and data base technology, as well as human computer interaction, but also include other areas, which contribute to visual analytics, such as statistical analysis, geographical data analysis and cognitive science. Most of the projects combine at least two different research areas. The goal is to develop new techniques, which are successfully used in a concrete application and show significant improvements over existing approaches.