KDI: Towards Ideal Data Representations

KDI：迈向理想的数据表示

• 批准号: 9872890
• 负责人: Amos Ron
• 金额: $ 250万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-10-01 至 2003-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9872890&HistoricalAwards=false
• 关键词: KDI; Towards; Ideal; Data; Representations

9872890Ron Advances in communication, sensing, and computational powerhave led to an explosion of data. The size and varied formats forthese datasets challenge existing techniques for transmission,storage, querying, display, and numerical manipulation, tothe point where limits on their accessibility and portability mayseverely restrict their usefulness for human knowledge. Thisoften leads to the paradoxical situation where experiments ornumerical computations produce rich, exquisitely detailedinformation, for which, at this point, no adequate analysistools exist. In order to address this challenge, theinvestigator and his colleagues develop a new technology for datarepresentation based on the two basic principles of multiscaledecompositions and redundant representations. Multiscaledecompositions arrange data into strata reflecting their relativeimportance. This allows for rapid access to good coarseresolution of the data while retaining the flexibility forincreasingly fine representations. Redundant representationsallow for a multitude of data decompositions. While this on thesurface appears contrary to the need for efficiency, theredundancy gives the flexibility of choosing `bestrepresentations' from a unified family of representers andthereby provides efficiency and robustness. The proposedresearch is expected to deliver major results for: (i) accuraterepresentation of image and acoustic data, (ii) parsimoniousrepresentation of high dimensional data, (iii) parsimoniousrepresentation of images and volumetric objects withsingularities along curves and surfaces, (iv) acceleration ofscientific/engineering computations. The KDI initiative takes place at a time when intellectualand commercial life are beginning to feel the effects of arevolutionary combination: sensor ubiquity, computationalubiquity, and internet connectivity. A clear priority in allfields of commercial, engineering, and scientific endeavor mustbe to identify and exploit the opportunities available in thisnew era. The center of the effort should be the intensivedevelopment of new schemes for representing digitally acquireddata, and for rapidly manipulating those representations. Infact, advances in this central area have tremendousrepercussions, accelerating progress in every other area. Forastronomers straining to detect faint gravitational signalscoming from the farthest reaches of the universe, or looking backin time to the earliest moments after creation, searching fortemperature fluctuations that would give clues about the centraltheories of physics; for geophysicists looking for subtledeformations in the earth's inner structure for clues about ourseismic future; for engineers developing new medical imagingdevices; even for Hollywood entrepreneurs wanting more realisticcomputer graphic simulations for mass entertainment -- datarepresentation plays a key role. To this end, this projectassembles a team of experts to address issues of developing newdata representations and new methods of analysis andmanipulation. The premise of this venture is that significantadvances in data representation require an interdisciplinaryeffort, meshing the skills and knowledge of theoreticians andpractitioners from varied fields of research that involve largedatasets. Thus, the proposed research team consists ofmathematicians, statisticians, computer scientists, and engineerswith extensive skills and experience in the development and useof representations for datasets. A primary component of theproject is the set of application areas in image and signalprocessing, large scale computation, and computer graphics. Theproject produces conceptual deliverables in the form of newmethods for storing, compressing, denoising, and querying data.It also produces concrete deliverables in the form of algorithmsand software for use in the scientific and commercial sector. Theproject serves as a national center for data representation.Interaction between the project and other national andinternational centers treating datasets is cultivated. Theproject also provides a national resource for theoreticaladvances, techniques of implementation, and software development.

9872890Ron 通信、传感和计算能力的进步导致了数据的爆炸式增长。 这些数据集的大小和不同的格式对现有的传输、存储、查询、显示和数值操作技术提出了挑战，以至于对其可访问性和可移植性的限制可能会严重限制它们对人类知识的有用性。 这常常导致一种矛盾的情况，即实验或数值计算产生丰富、精致的详细信息，但目前还没有足够的分析工具。 为了应对这一挑战，研究人员和他的同事基于多尺度分解和冗余表示两个基本原理开发了一种数据表示新技术。 多尺度分解将数据排列成反映其相对重要性的层。 这允许快速访问数据的良好粗分辨率，同时保留日益精细的表示的灵活性。 冗余表示允许大量数据分解。 虽然这表面上看来与效率的需要相反，但冗余提供了从统一的表示家族中选择“最佳表示”的灵活性，从而提供了效率和鲁棒性。 拟议的研究预计将在以下方面取得主要成果：（i）图像和声学数据的准确表示，（ii）高维数据的简约表示，（iii）沿曲线和表面具有奇异性的图像和体积对象的简约表示，（iv）科学/工程计算的加速。 KDI 倡议发生之际，知识和商业生活开始感受到革命性组合的影响：传感器无处不在、计算无处不在和互联网连接。 商业、工程和科学努力的所有领域的一个明确的优先事项必须是识别和利用这个新时代的机会。 工作的中心应该是集中开发用于表示数字获取的数据并快速操纵这些表示的新方案。 事实上，这一中心领域的进步会产生巨大的影响，加速其他所有领域的进步。 对于天文学家来说，他们努力探测来自宇宙最远距离的微弱引力信号，或者回顾宇宙诞生后的最早时刻，寻找温度波动，从而为物理学的核心理论提供线索；对于地球物理学家来说，寻找地球内部结构的微妙变形，以寻找有关我们地震未来的线索；供工程师开发新型医学成像设备； 即使对于希望为大众娱乐提供更真实的计算机图形模拟的好莱坞企业家来说，数据表示也起着关键作用。 为此，该项目组建了一个专家团队来解决开发新数据表示以及新分析和操作方法的问题。 这项事业的前提是，数据表示方面的重大进步需要跨学科的努力，将涉及大型数据集的不同研究领域的理论家和实践者的技能和知识结合起来。 因此，拟议的研究团队由数学家、统计学家、计算机科学家和工程师组成，他们在开发和使用数据集表示方面拥有丰富的技能和经验。 该项目的主要组成部分是图像和信号处理、大规模计算和计算机图形学方面的应用领域集。 该项目以存储、压缩、去噪和查询数据的新方法的形式产生概念性成果，还以算法和软件的形式产生具体的成果，供科学和商业领域使用。 该项目作为国家数据表示中心。该项目与处理数据集的其他国家和国际中心之间的互动得到了培养。 该项目还为理论进步、实施技术和软件开发提供了国家资源。