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

SPP 1335：可扩展的视觉分析：复杂信息空间的交互式视觉分析系统

• 批准号: 43045503
• 金额: --
• 依托单位: Arbeitsgruppe Datenanalyse und Visualisierung
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2008
• 资助国家: 德国
• 起止时间: 2007-12-31 至 2017-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/43045503?language=en
• 关键词: SPP; 1335; Scalable; Visual; Analytics

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.

在研究和开发以及在许多应用领域中产生了具有快速增长的复杂性和动态性的数据集。一个核心挑战是检测重要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。只有通过数据分析和可视化技术的结合，才有可能有效地访问否则难以管理的复杂数据集。视觉分析技术使意想不到的事情更容易被发现，并有助于获得新的见解。视觉分析领域的主要目标是以一种可以容易地检测到数据的结构联系、相关特征和其他有趣属性的方式来图形化地表示真实或抽象的数据。优先方案的重点是研究新的视觉分析算法的理论基础、可伸缩视觉分析技术的开发和实际实施，以及它们的整合和评价。一个核心挑战是可伸缩性，这不仅与数据集的大小有关，而且与数据的重要属性有关，如维度、生产率、同质性、现实性、精确度和完整性。此外，视觉分析技术本身应该是可扩展的，这意味着它们应该是交互的，并传达数据的质量和相关性。视觉分析方法的可扩展性只有通过来自计算机科学不同领域的科学家之间的密切合作才能实现。优先方案的参与者来自可视化、数据分析和数据库技术以及人机交互等研究领域，但也包括有助于视觉分析的其他领域，如统计分析、地理数据分析和认知科学。大多数项目至少结合了两个不同的研究领域。我们的目标是开发新的技术，这些技术在具体的应用中得到了成功的应用，并显示出对现有方法的重大改进。