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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：
1637320
负责人：
Judith Cushing
金额：
$ 13.72万
依托单位：
Evergreen State College
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：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637320&HistoricalAwards=false
关键词：
EAGER Collaborative Research Connecting Communities

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制作可视化，并向其他科学家和包括决策者在内的利益相关者展示。迄今为止工作的一个关键发现是，科学家不仅在多大程度上利用可视化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。科学可视化在知识共同生产中的作用尚未得到检验，尽管这种参与可能对创造可接受的解决方案、信息或技术至关重要。该提案将vista改造为共同生产可视化工具，即探索用户之间如何进行谈判？需求和技术能力塑造了所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。这是一项独特的实验，是社会、计算机和环境科学家与非科学家利益相关者之间的合作，共同产生用于决策的数据可视化。社会科学方法将用于探索知识合作生产与技术创新相结合，从而导致社区决策解决气候变化适应问题。将确定科学家和非科学家的科学可视化之间需要区分的程度，并将与项目合作者共同开发独特的可视化。目标是确定可视化对科学家和利益相关者在与气候适应有关的关键决策中共同生产知识的影响。这个项目涉及计算机科学家和社会科学家。计算机科学：vista是一个c++科学可视化应用程序，具有重要的GPU处理功能，可以帮助环境科学家生成图像，使他们能够“看到”。地形对生态现象的影响。对于该奖项，将开发新的可视化技术，进行可视化和可视化分析研究，使决策者能够有效地进行演示，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，将对现有软件进行扩展，使其更易于主要用户和次要用户使用，并且更易于主要用户直接维护和扩展：vista工程师将继续从c++迁移到Python的长期战略，这将使更有效和灵活的用户界面开发，最终用户编程的数据或可视化插件，并使用新兴的和现有的Python和R库进行可视化分析。社会科学方面的调查将有助于确定，联合生产如何使可用的软件既能满足产生大量难以解释的数据集的环境科学家的需求，也能满足在做出重要选择时必须平衡多种需求的决策者的需求。在与利益相关者合作共同开发可用信息时，将与三名合作者进行案例研究；通过三个阶段的比较前/后测试设计来构建这些测试，以探索参与者在参与可视化开发之前和之后如何看待和交流科学结果的变化。在基线阶段，vista社会科学家将与参与者一起记录他们目前对数据的理解，对可视化和分析产品的期望，以及用于与他人（包括非科学家）交流科学的能力和工具。在开发阶段，案例参与者将在一起创建可视化和分析产品时被观察到。评估后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。信息将主要通过与参与者（合作者和利益相关者）的半结构化访谈来收集。将使用现有的测量环境态度和决策中对科学的偏好以及对科学的一般态度的量表，以便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，以确定如何开发对用户需求的共同理解，然后将其框定为可视化问题。