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Digital Government: Collaborative Research: Quality Graphics for Federal Statistics

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
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-08-15 至 2005-02-28

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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.
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