EAGER: Collaborative Research: Connecting Communities Through Data, Visualizations, and Decisions
EAGER:协作研究:通过数据、可视化和决策连接社区
基本信息
- 批准号:1637334
- 负责人:
- 金额:$ 10.26万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-01 至 2019-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The Visualization for Terrestrial and Aquatic Systems project helps environmental scientists produce visualizations for their own research and for presentation to other scientists and stakeholders including decision makers. A critical finding of work to date is the extent to which scientists use visualizations not only to explore data in new ways and present results, but also to work with stakeholders to jointly produce information that can be used during decision-making processes. The role of scientific visualization in the co-production of knowledge is as yet untested, even though this involvement could be critical in creating acceptable solutions, information, or technology. This proposal recasts VISTAS to co-produce visualization tools, i.e., exploring how negotiations between the users? needs and technological capacity shape the type of visualizations used and tools implemented, change or modify the research questions posed by scientists, and impact how results are interpreted so communities can respond to critical ecological challenges, including climate change. This is a unique experiment and collaboration among social-, computer-, and environmental scientists, with non-scientist stakeholders, to co-produce data visualizations for use in decision making. Social science methods will be used to explore knowledge co-production coupled with technology innovations that lead to community decision making to solve problems of climate change adaptation. The extent to which distinctions between scientific visualization for scientists and non-scientists need to be made will be determined, and unique visualizations will be developed jointly with project collaborators. The goal is to determine the influence of visualization on the co-production of knowledge among scientists and stakeholders on critical decisions related to climate adaptation. This project involves both computer scientists and social scientists. Computer science: VISTAS, a C++ scientific visualization application with significant GPU processing, helps environmental scientists produce images that allow them to ?see? the effects of topography on ecological phenomena. For this award, new visualization techniques will be developed, visualization and visual analytics research that enables effective presentations to decision makers will be conducted, and technical support for environmental- and social scientists will be provided. If time and funds permit extensions to the current software that render it both more usable by primary and secondary users, and more maintainable and extensible directly by primary users will be provided: VISTAS engineers will proceed with a longer term strategy of migrating from C++ to Python, which will enable more effective and flexible user interface development, end user programming of data or visualization plug-ins, and use of emerging and existing Python and R libraries for visual analytics. The social science inquiry will help determine how the co-production enables usable software that answers the needs of both environmental scientists who generate large difficult to interpret data sets as well as decision-makers who must balance multiple demands as they make important choices. Case studies with three collaborators will be conducted as they work with stakeholders to co-develop usable information; these are structured through a comparative pre/post-test design with three phases to explore changes in how participants view and communicate scientific results before and after involvement in visualization development. In the baseline phase VISTAS social scientists will work with participants to document their current understanding of their data, expectations for the visualization and analytic products, and ability and tools used to communicate science to others including non-scientists. During the development phase case participants will be observed as they work together to create the visualization and analytic products. The post-assessment phase seeks to determine changes in understanding of data and ability to communicate science as a result of participation in visualization development. The usability of different types of visualizations and analytic tools, identifying the characteristics that contribute to or distract from usefulness, will also be explored. Information will be collected primarily through semi-structured interviews with participants (collaborators and stakeholders). Existing scales measuring environmental attitudes and preferences for science in decision-making and general attitudes toward science will be used so comparisons with larger national and international samples can be made. In addition, scoping and development meetings will be observed to determine how shared understanding of user needs is developed and then framed as a visualization problem.
陆地和水生系统可视化项目帮助环境科学家为他们自己的研究和向其他科学家和包括决策者在内的利益攸关方提供可视化。 迄今为止的一个关键工作发现是,科学家在多大程度上不仅使用可视化来以新的方式探索数据并呈现结果,而且还与利益相关者合作,共同产生可在决策过程中使用的信息。 科学可视化在知识的共同生产中的作用尚未得到验证,尽管这种参与对于创造可接受的解决方案,信息或技术至关重要。 该提案将VISTAS重塑为共同制作可视化工具,即,探讨用户之间如何谈判?需求和技术能力决定了使用的可视化类型和实施的工具,改变或修改了科学家提出的研究问题,并影响了如何解释结果,以便社区能够应对包括气候变化在内的关键生态挑战。 这是社会科学家、计算机科学家和环境科学家与非科学家利益相关者之间的独特实验和合作,共同制作用于决策的数据可视化。 社会科学的方法将被用来探索知识的共同生产加上技术创新,导致社区决策,以解决气候变化适应的问题。 将确定科学家和非科学家的科学可视化之间的区别,并与项目合作者共同开发独特的可视化。其目标是确定可视化对科学家和利益攸关方共同制作与气候适应有关的关键决策的知识的影响。这个项目涉及计算机科学家和社会科学家。 计算机科学:VISTAS是一个具有重要GPU处理能力的C++科学可视化应用程序,可帮助环境科学家生成图像,使他们能够?看到没?地形对生态现象的影响。 该奖项将开发新的可视化技术,进行可视化和可视化分析研究,以便向决策者进行有效的演示,并为环境和社会科学家提供技术支持。 如果时间和资金允许对目前的软件进行扩展,使其对主要用户和次要用户都更有用,并提供更多的主要用户直接维护和扩展:VISTAS工程师将继续从C++迁移到Python的长期战略,这将实现更有效和灵活的用户界面开发,数据或可视化插件的最终用户编程,以及使用新兴和现有的Python和R库进行可视化分析。社会科学调查将有助于确定联合生产如何实现可用的软件,以满足环境科学家的需求,这些环境科学家生成了大量难以解释的数据集,而决策者在做出重要选择时必须平衡多种需求。 与三个合作者的案例研究将进行,因为他们与利益相关者合作,共同开发可用的信息;这些是通过比较前/后测试设计的三个阶段,以探索参与者如何查看和交流可视化开发之前和之后的科学结果的变化。在基线阶段,VISTAS社会科学家将与参与者合作,记录他们目前对数据的理解,对可视化和分析产品的期望,以及用于向包括非科学家在内的其他人传达科学的能力和工具。在开发阶段,将观察案例参与者,因为他们一起工作,以创建可视化和分析产品。后评估阶段旨在确定参与可视化开发后对数据的理解和科学传播能力的变化。还将探讨不同类型的可视化和分析工具的可用性,确定有助于或分散有用性的特征。 将主要通过与参与者(合作者和利益攸关方)的半结构化访谈收集信息。现有的尺度测量环境的态度和偏好的科学决策和对科学的一般态度将被用来与更大的国家和国际样本进行比较。此外,将观察范围界定和开发会议,以确定如何形成对用户需求的共同理解,然后将其框定为可视化问题。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Denise Lach其他文献
Denise Lach的其他文献
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{{ truncateString('Denise Lach', 18)}}的其他基金
Collaborative Research: ABI Development: RUI: From Data to Knowledge in Grand Challenge Environmental Science Research: VISTAS
合作研究:ABI 开发:RUI:大挑战中从数据到知识环境科学研究:VISTAS
- 批准号:
1062566 - 财政年份:2011
- 资助金额:
$ 10.26万 - 项目类别:
Continuing Grant
Changing Expectations for Science and Scientists in Natural Resource Decision Making: A Case Study of the Long Term Ecological Research (LTER) Program
科学和科学家对自然资源决策的期望不断变化:长期生态研究 (LTER) 计划案例研究
- 批准号:
0427494 - 财政年份:2004
- 资助金额:
$ 10.26万 - 项目类别:
Continuing Grant
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