Visualization is a widely used and effective means of communicating information about complex relationships among variables, their geographic distributions, and of how those distributions change through time. Visualizations that are interactive (e.g. giving the user control over viewing perspective, display characteristics, and access to related statistical information) and animated (e.g. able to display change through time as a seamless sequence) comprise an intuitive environment for interrogating databases, extracting knowledge, and for formulating explanatory and other hypotheses. Most web- GIS employ a centralized architecture that sends graphics and queries over the www. Because of slow communication protocols this architecture is inherently incapable of supporting real-time interaction between the user, the visualization engine, and the georeferenced database. This project employs two new technologies, Space-Time Information Systems (STIS) and WebBots to develop an open-source system for Omicron Interactive visualization of space-time change in cancer mortality patterns, and the uncertainties associated with those mortalities; Omicron Exploring multivariate relationships in cancer mortality as a function of spatial scale. This open-source system will be disseminated over the www, and is ultimately expected to increase our understanding of how mortality from different cancers covary, with one another, through space, and through time.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA092669-03
Application #
6646577
Study Section
Special Emphasis Panel (ZRG1-SNEM-2 (02))
Program Officer
Tiwari, Ram C
Project Start
2001-09-12
Project End
2005-08-31
Budget Start
2003-09-01
Budget End
2005-08-31
Support Year
3
Fiscal Year
2003
Total Cost
$350,675
Indirect Cost
Name
Biomedware
Department
Type
DUNS #
947749388
City
Ann Arbor
State
MI
Country
United States
Zip Code
48103
Meliker, Jaymie R; AvRuskin, Gillian A; Slotnick, Melissa J et al. (2008) Validity of spatial models of arsenic concentrations in private well water. Environ Res 106:42-50
Meliker, Jaymie R; Slotnick, Melissa J; Avruskin, Gillian A et al. (2007) Individual lifetime exposure to inorganic arsenic using a space-time information system. Int Arch Occup Environ Health 80:184-97
Jacquez, Geoffrey M; Kaufmann, Andy; Meliker, Jaymie et al. (2005) Global, local and focused geographic clustering for case-control data with residential histories. Environ Health 4:4
Greiling, Dunrie A; Jacquez, Geoffrey M; Kaufmann, Andrew M et al. (2005) Space-time visualization and analysis in the Cancer Atlas Viewer. J Geogr Syst 7:67-84
Goovaerts, Pierre; Jacquez, Geoffrey M; Greiling, Dunrie (2005) Exploring scale-dependent correlations between cancer mortality rates using factorial kriging and population-weighted semivariograms. Geogr Anal 37:152-182
Goovaerts, Pierre; Jacquez, Geoffrey (2004) Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York. Int J Health Geogr 3:14
Jacquez, Geoffrey (2004) Current practices in the spatial analysis of cancer: flies in the ointment. Int J Health Geogr 3:22
Avruskin, Gillian; Jacquez, Geoffrey; Meliker, Jaymie et al. (2004) Visualization and exploratory analysis of epidemiologic data using a novel space time information system. Int J Health Geogr 3:26
Jacquez, Geoffrey; Greiling, Dunrie (2003) Geographic boundaries in breast, lung and colorectal cancers in relation to exposure to air toxics in Long Island, New York. Int J Health Geogr 2:4
Jacquez, Geoffrey; Greiling, Dunrie (2003) Local clustering in breast, lung and colorectal cancer in Long Island, New York. Int J Health Geogr 2:3