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A Study of Knowledge-Intensive Visualization System

知识密集型可视化系统研究

基本信息

批准号：
17300029
负责人：
SHIRAYAMA Susumu
金额：
$ 9.82万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2005
资助国家：
日本
起止时间：
2005 至 2007
项目状态：
已结题

项目摘要

Development of high-performance personal computing and the spread of broadband service may mean that a huge amount of data is produced from a personal site, and useful computational data is accumulated and distributed over personal sites.Owing to the volume of data, it is quite difficult to extract useful information from these data even if using scientific/information visualization techniques. In this study, a flexible visualization methodology based on "analysis of visualization process" is introduced. And we have developed a new knowledge-intensive visualization system to overcome the above-mentioned issues.First, we summarized the basic requirements of our system from users' evaluations of conventional visualization system and needs for future system. Secondly, we pointed out the importance of structurization of process of data generation and data management, and formulation of data definitions. Thirdly, we have developed major components of the system as follows:1. intelligent space for the analysis of visualization process,2. synthetic visualization technique for scientific and information visualization,3. new technique to retrieve a grid data based on the characteristic feature of grid data,4. image recording technique has the capability to preserve for long-term.And then,5. An efficient isosurfacing technique based on human visual recognition,6. An annotation system based on visual attention,7. A visualization agent designed from a process model helps to reduce the difficulty of handling huge data, are considered.A part of the system is released as public domain software. It will be expected that the visualized information produced from our system can be preserved as an intellectual asset in long time.

高性能个人计算的发展和宽带服务的普及可能意味着从个人网站产生大量数据，有用的计算数据积累并分布在个人网站上，由于数据量大，即使使用科学/信息可视化技术也很难从这些数据中提取有用的信息。在本研究中，提出了一种基于“可视化过程分析”的灵活的可视化方法。为了克服上述问题，我们开发了一种新的知识密集型可视化系统。首先，根据用户对传统可视化系统的评价和对未来系统的需求，总结了本系统的基本要求。其次，指出了数据生成和数据管理过程的结构化以及数据定义的制定的重要性。系统的主要组成部分如下：1.用于可视化过程分析的智能空间；2.科学与信息可视化的综合可视化技术；3.基于栅格数据特征的栅格数据检索新技术；4.具有长期保存能力的图像记录技术；5.基于人类视觉识别的高效等值面技术；6.基于视觉注意力的标注系统；7.基于过程模型设计的可视化代理，以降低处理海量数据的难度。系统的一部分以公共领域软件的形式发布。预计从我们的系统产生的可视化信息可以作为一种智力资产长期保存。