CAREER: Picturing Motion: Analyzing Multidimensional Time-Varying Data through Perceptually Accurate Exploratory Visualization
CAREER: Picturing Motion: Analyzing Multidimensional Time-Varying Data through Perceptually Accurate Exploratory Visualization
批准号:
1054783
负责人:
Daniel Keefe
金额:
$46.7万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-02-01 至 2018-01-31
中文摘要
该研究项目的目标是改变使用计算机分析复杂时变科学现象的方式。 该项目使得对大型、高分辨率的科学运动数据库进行聚合和比较分析成为可能。 该方法将人类视觉系统的高带宽通道与计算算法和交互式数据探索相结合。实验研究与教育工作相结合,包括通过新课程,新的以写作为重点的课程和广泛传播的课程计划来培训计算机科学家学生进行跨学科研究。 艺术家和设计师是研究的直接参与者,为视觉创意学生开辟了科学领域的新职业道路。 动手互动可视化从事7- 12年级少数民族和贫困学生在科学计算。 结果包括实验接地指南感知准确的可视化,耦合降维与说明性数据可视化的新技术,并测试人机界面探索空间复杂的多维数据。 这些结果意义重大,因为它们导致了对人与计算之间耦合关系的新理解,特别是帮助科学家从庞大复杂的数据集转向新的见解。 这项工作的更广泛影响在于应用于多个学科,包括肌肉骨骼生物力学,进化生物学和地理空间科学。通过具体的应用,这项工作产生的见解可能导致改善儿童和成人脊柱疾病和疾病的治疗,并为动物历史多样化的新理论提供信息。 项目成果将通过开放源码软件、录像、出版物和演示进行传播,所有这些都可在项目网站上查阅(http://www.cs.umn.edu/NSFkeefe/NSFCAREER)。
英文摘要
The goal of this research project is to transform the way that complex time-varying scientific phenomena are analyzed using computers. The project makes possible a new style of aggregate and comparative analysis of large, high-resolution scientific motion databases. The approach combines the high-bandwidth channel of the human visual system with computational algorithms and interactive data exploration.The experimental research is integrated with educational efforts, including training computer scientist students in interdisciplinary research via a new course, a new writing-focused curriculum, and broadly disseminated lesson plans. Artists and designers are direct participants in the research, opening up new career paths in the sciences for visually creative students. Hands-on interactive visualizations engage 7-12th grade minority and underprivileged students in scientific computing. The results include experimentally grounded guidelines for perceptually accurate visualization, new techniques for coupling dimensionality reduction with illustrative data visualization, and tested human-computer interfaces for exploring spatially complex multidimensional data. These results are significant because they lead to new understandings of the coupled relationship between people and computing, specifically helping scientists move from vast, complex datasets to new insights. The broader impacts of the work lie in applications to multiple disciplines including musculoskeletal biomechanics, evolutionary biology, and geospatial science. Through specific applications, the work yields insights that could lead to improved treatments for spinal disorders and diseases in children and adults, and inform new theories of historical diversification among animals. Project results will be disseminated via open source software, videos, publications, and demos, all available on the project web site (http://www.cs.umn.edu/~keefe/NSFCAREER).
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会议论文
Collaborative Research: HCC: Small: RUI: Drawing from Life in Extended Reality: Advancing and Teaching Cross-Reality User Interfaces for Observational 3D Sketching
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批准号:2326998
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项目类别:Standard Grant
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资助金额:$40.0万
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财政年份:2023
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负责人:Daniel Keefe
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依托单位:
CHS: Medium: Collaborative Research: Sculpting Visualizations: Toward a Practice and Theory of 3D Scientific Visualizations Using Physical Objects and Augmented Reality
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批准号:1704604
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项目类别:Continuing Grant
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资助金额:$67.5万
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财政年份:2017
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负责人:Daniel Keefe
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依托单位:
WORKSHOP: IEEE VR 2014 Doctoral Consortium
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批准号:1416888
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项目类别:Standard Grant
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资助金额:$1.56万
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财政年份:2013
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负责人:Daniel Keefe
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依托单位:
BIGDATA: Small: DA: Coupling Data-Intensive Modeling, Simulation, and Visualization with Human Facilities for Design: Applications to Next-Generation Medical Device Prototyping
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批准号:1251069
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项目类别:Standard Grant
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资助金额:$50.1万
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财政年份:2013
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负责人:Daniel Keefe
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依托单位:
CGV: Small: Visualization by Sketching, Analogy, and Computational Creativity
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批准号:1218058
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项目类别:Standard Grant
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资助金额:$43.21万
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财政年份:2012
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负责人:Daniel Keefe
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依托单位:
海外基金