Communications of the ACM
Nih Seeking Advances in Spatial ncertainty
The headquarters of the National Institutes of Health.
Credit: gwmed.com
The U.S. National Institutes of Health (NIH) recently issued a solicitation for innovative research that identifies sources of spatial uncertainty in public health data, incorporates the inaccuracy into statistical methods, and develops tools to visualize the nature and consequences of the spatial uncertainty.
NIH says spatial uncertainty takes one or a combination of several forms. For example, geocoding is a procedure that converts information about the locations of people, homes, and other entities to geographic coordinates. In population-based public health data, geocoding is commonly obtained by an automated procedure and the results are well known to contain positional errors. To protect people's privacy, geographic information in disease data is usually not released, which results in gaps or incompleteness in data.
Spatial uncertainty also appears when data come through a variety of collection schemes at varying spatial scales. Boundaries of spatial units can evolve across time, which adds another layer of mismatches to a spatio-temporal level, according to NIH. In addition, NIH is seeking statistical methods to model spatial uncertainty, as well as new geographic information system methods for addressing and visualizing spatial uncertainty.
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