Digital Government: Collaborative Research: Quality Graphics for Federal Statistics

数字政府：协作研究：联邦统计的质量图形

• 批准号: 9983451
• 负责人: Alan MacEachren
• 金额: $ 33.07万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-15 至 2005-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9983451&HistoricalAwards=false
• 关键词: Digital; Government; Collaborative; Research; Quality

EIA-9983451MacEachren, Alan M.Pennsylvania State UniversityDigital Government: Collaborative Research: Quality Graphics for Federal Statistical SummariesThe Federal government distributes a vast quantity of statistical summaries in printed and electronic form. The full wealth of information that might be derived from these summaries is not being realized because limited attention is paid to disseminating summaries in understandable forms. This research will develop and assess quality graphics for federal statistical summaries. The development and assessment process will consider perceptual and cognitive factors in reading, interacting with and interpreting statistical graphs, maps and metadata representatives. The purposes of the quality graphics include exploration by agency users evaluating data quality and looking for emergent trends, decision making by public policy makers and communication of statistical summaries to the public. The proposed research addresses four topic areas: converting tables to graphs, representing metadata, interacting with both graphs and maps, and conveying multivariate spatial and temporal relationships. The research features use of Web-based "middleware" components to provide rapid development of graphics for usability testing. The featured middleware is a Java Graphics Component Library (GPL). A long history of research has recently culminated in a rigorous graph algebra that is the foundation for the library. The library also benefits from the collective intellectual effort being poured into Java. Principles of human perception and cognition will be used to guide the construction of statistical graphics, and usability tests will help to refine those principles in the context of federal statistical summaries. The research team has been carefully selected to bring together outstanding and compatible investigators who will provide expertise in statistical graphics, cartography, human perception and cognition, and software development and is composed of university, industrial and federal agency personnel.

EIA-9983451 MacEachren，Alan M.宾夕法尼亚州立大学数字政府：合作研究：联邦统计摘要的质量图形联邦政府以印刷和电子形式分发大量的统计摘要。 由于对以可理解的形式传播摘要的注意有限，因此没有充分利用这些摘要可能提供的丰富信息。 这项研究将为联邦统计摘要开发和评估高质量的图形。 开发和评估过程将考虑阅读中的感知和认知因素，与统计图表，地图和元数据代表进行交互和解释。 质量图表的目的包括机构用户评估数据质量和寻找新趋势的探索，公共政策制定者的决策以及向公众传达统计摘要。 拟议的研究涉及四个主题领域：将表格转换为图形，表示元数据，与图形和地图交互，以及传达多变量空间和时间关系。 研究的特点是使用基于Web的“中间件”组件，以提供快速开发的图形可用性测试。 该中间件是一个Java图形组件库（GPL）。 一个长期的研究历史最近达到高潮，在一个严格的图代数，是图书馆的基础。 该库还受益于Java的集体智力成果。 人类感知和认知的原则将用于指导统计图表的构建，可用性测试将有助于在联邦统计摘要的背景下完善这些原则。 该研究小组经过精心挑选，汇集了优秀和兼容的调查人员，他们将提供统计图形，制图，人类感知和认知以及软件开发方面的专业知识，并由大学，工业和联邦机构人员组成。