III: Small: Technologies for Creating Explanatory and Exploratory Animations from Scientific Data

III：小：根据科学数据创建解释性和探索性动画的技术

• 批准号: 1528203
• 负责人: Kwan-Liu Ma
• 金额: $ 50万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1528203&HistoricalAwards=false
• 关键词: III; Small; Technologies; Creating; Explanatory

Animation is a powerful, expressive medium for visual explanations and for telling stories with data. Scientists make extensive use of animations to explain their findings and to illustrate complex phenomena. By presenting time as time, animation is one of the most natural ways to illustrate how objects evolve and interact, and how they change in shape, size, position, and spatial relationship to other objects over time. Both commercial and open-source visualization tools offer a wealth of visualization techniques, enabling scientists to explore their data and to generate individual images to capture key aspects of the subject under study. However, most visualization packages include very limited support for creating explanatory animations. As a result, scientists who wish to use animations to illustrate their findings must spend considerable amounts of time learning how to produce animations, often using external software packages, or turn to professional animators or production specialists for assistance. This research aims to develop adequate support for composing animation content and constructing scientific video narratives, and also extend explanatory animation to exploratory animation and study its usability. This project will thus have a significant impact on both the visualization researchers and users in a range of domains, including education. The new concepts introduced in this project will inspire others to also develop similar and even better support for scientific storytelling using visualization. More users will benefit from such advanced visualization technologies leading to high productivity in their work, or support educational and outreach activities. The research team will continue collaboration with a science museum to seek the opportunities to convert explanatory/exploratory animations into interactive exhibits. Research will be integrated into teaching, in the form of special topic courses, the establishment of internships with industry and national laboratories, and the introduction of visualization technology to students from other disciplines. The project will provide an environment for research training for graduate and undergraduate students. This research will introduce key technologies that can greatly increase scientists' ability to make visualization animations and video narratives for storytelling. To facilitate scientific narrations using animations, this project will design a semi-automatic animation generation system tightly coupled with the interactive data exploration and visualization process. That is to make the process of animation and storytelling a first class citizen within exploratory data visualization tools. This will allow the scientists to focus on gaining insight from their data, and the visualization tools should assist them in assembling findings together into a coherent story for presentation. This project will design methods to choose views, camera paths, lighting, transitions, etc. for users. Methods for users to interact with animations will also be designed, instead of passively watching, to achieve new levels of inspection and apprehension. Explorable images, a powerful and novel concept introduced for realizing exploratory animation, enables multidimensional data exploration using a medium comparable to a video in terms of compactness and simplicity. The task of realizing these novel concepts and designs, and integrating them into scientists' workflows and tools, will be challenging. This research will conduct extensive evaluation of the animation support, with the participation of domain scientists who are prospective users of the new technology. The lessons learned in this project may establish guidelines for the effective use of animation in explaining complex phenomena, and suggest a new framework for next-generation visualization systems. The project web site (http://vis.cs.ucdavis.edu/NSF/IIS1528203) will provide access to research results, including data and prototype software.

动画是一种强大的、富有表现力的媒介，用于视觉解释和用数据讲述故事。科学家们广泛使用动画来解释他们的发现，并说明复杂的现象。通过将时间表示为时间，动画是说明对象如何演变和交互，以及它们如何随着时间的推移在形状、大小、位置和与其他对象的空间关系方面发生变化的最自然的方式之一。商业和开源可视化工具都提供了丰富的可视化技术，使科学家能够探索他们的数据并生成单独的图像，以捕捉正在研究的主题的关键方面。然而，大多数可视化包对创建解释性动画的支持非常有限。因此，希望使用动画来说明他们的发现的科学家必须花费大量时间学习如何制作动画，通常使用外部软件包，或者向专业动画师或制作专家寻求帮助。本研究旨在为创作动画内容和构建科学的视频叙事提供足够的支持，并将解释性动画扩展到探索性动画，并研究其可用性。因此，该项目将对可视化研究人员和包括教育在内的一系列领域的用户产生重大影响。这个项目中引入的新概念将激励其他人也开发类似的、甚至更好的支持使用可视化的科学故事讲述。更多的用户将受益于这种先进的可视化技术，从而提高他们的工作效率，或支持教育和外联活动。研究小组将继续与一家科学博物馆合作，寻找机会将说明性/探索性动画转化为互动展品。研究将以专题课程的形式融入教学，在行业和国家实验室设立实习机会，并向其他学科的学生介绍可视化技术。该项目将为研究生和本科生提供一个研究培训的环境。这项研究将介绍关键技术，这些技术可以极大地提高科学家为讲故事制作可视化动画和视频叙事的能力。为了便于使用动画进行科学叙述，本项目将设计一个与交互式数据探索和可视化过程紧密结合的半自动动画生成系统。也就是说，让动画和讲故事的过程成为探索性数据可视化工具中的一等公民。这将使科学家能够专注于从他们的数据中获得洞察力，可视化工具应该帮助他们将发现组合在一起，形成一个连贯的故事来展示。该项目将设计方法来选择视图，相机路径，照明，过渡等为用户。还将设计用户与动画互动的方法，而不是被动观看，以实现新的检查和理解水平。可探索图像是为实现探索性动画而引入的一个强大而新颖的概念，它允许使用在紧凑性和简单性方面可与视频相媲美的媒介进行多维数据探索。实现这些新概念和设计，并将它们整合到科学家的工作流程和工具中，这将是一项具有挑战性的任务。这项研究将对动画支持进行广泛的评估，参与评估的领域科学家是这项新技术的潜在用户。从这个项目中学到的经验教训可能会为有效地使用动画解释复杂现象建立指导方针，并为下一代可视化系统提出一个新的框架。该项目的网站(http://vis.cs.ucdavis.edu/NSF/IIS1528203))将提供对研究结果的访问，包括数据和原型软件。