GV: Small: Collaborative Research: Supporting Knowledge Discovery through a Scientific Visualization Language

GV：小型：协作研究：通过科学可视化语言支持知识发现

• 批准号: 1302755
• 负责人: Jian Chen
• 金额: $ 16.06万
• 依托单位: University of Maryland Baltimore County
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-31 至 2015-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1302755&HistoricalAwards=false
• 关键词: GV; Small; Collaborative; Research; Supporting

This collaborative research brings together computer scientists from University of Maryland Baltimore County (UMBC) and Brown University and neuroscientists from the University of Mississippi Medical Center (UMMC) to study the design of a scientific visualization language (SVL). Despite the numerous visualization approaches already devised, visualization remains more of an art than a science. Grounded in theories and methods from human-centered computing, machine learning, and cognitive psychology, this work is to develop and evaluate a scientific visualization language (SVL) to provide a principled way to help scientists understand how and why visualizations work. Tools and theories developed in this project can lead to efficient knowledge discovery to help neuroscientists study brains using diffusion tensor magnetic resonance imaging (DTI).This work has the following specific objectives and outcomes: (1) close collaboration with scientists to discover, refine, and verify a symbol space, (2) a semantic space that describes the relationship among symbols, (3) a testbed that implements SVL for neuroscientists to compose visualizations, (4) development of new and enhanced courses at University of Southern Mississippi and Brown University, and (5) wide dissemination of the research outcomes through open-source software, experimental data, open labs, publications, and presentations.This project is expected to have broad impact. It may lead to significantly better approaches to human knowledge discovery and decision making in many disciplines where visualizations have found successful application, including neuroscience, biomedicine, bioinformatics, biology, chemistry, geosciences, business, economics, and education. Undergraduate and graduate students are expected to participate in the research through our courses, and student exchanges are planned between USM and Brown. K-12 students can visit the USM lab while the project is in progress. Software and results will be disseminated via the project Web site (https://sites.google.com/site/simplevisualizationlanguage).