Supporting visual analysis of federal geospatial statistics

Alan M. MacEachren; Frank Hardisty; Xiping Dai; Linda Pickle

doi:10.1145/602421.602452

Supporting visual analysis of federal geospatial statistics

Alan M. MacEachren, Frank Hardisty, Xiping Dai, Linda Pickle

Geography

Research output: Contribution to journal › Review article › peer-review

12 Scopus citations

Abstract

The efforts toward linking of Federal government agencies' statistical data through common geospatial referencing are discussed. Research is focused on human-centered design and implementation of component-based tools that help agency analysts to identify errors, anomalies, clusters and possible multivariate relationships. Specific aim in the digital government research has been to develop and assess components that support highly interactive visual data analysis. Effective data analysis components have been developed integrating them into applications to assess usefulness and usability of those applications.

Original language	English (US)
Pages (from-to)	59-60
Number of pages	2
Journal	Communications of the ACM
Volume	46
Issue number	1
DOIs	https://doi.org/10.1145/602421.602452
State	Published - Jan 2003

All Science Journal Classification (ASJC) codes

General Computer Science

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10.1145/602421.602452

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Supporting visual analysis of federal geospatial statistics

Abstract

All Science Journal Classification (ASJC) codes

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