A first step towards a framework for presenting the location of confidential point data on maps—results of an empirical perceptual study
Michael Jay Leitner, Andrew Curtis
Abstract
Michael Jay Leitner, Andrew Curtis
Abstract
A common concern when working with health‐related data is that national standard guidelines are designed to preserve individual statistical information, usually recorded as text or in a spreadsheet format (‘statistical confidentiality’), but lack appropriate rules for visualizing this information on maps (‘spatial confidentiality’). Privacy rules to protect spatial confidentiality become more and more important, as governmental agencies increasingly incorporate Geographic Information Systems (GIS) as a tool for collecting, storing, analysing, and disseminating spatial information. The purpose of this paper is to propose the first step of a general framework for presenting the location of confidential point data on maps using empirical perceptual research. The overall objective is to identify geographic masking methods that preserve both the confidentiality of individual locations, and at the same time the essential visual characteristics of the original point pattern.
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A common concern when working with health‐related data is that national standard guidelines are designed to preserve individual statistical information, usually recorded as text or in a spreadsheet format (‘statistical confidentiality’), but lack appropriate rules for visualizing this information on maps (‘spatial confidentiality’). Privacy rules to protect spatial confidentiality become more and more important, as governmental agencies increasingly incorporate Geographic Information Systems (GIS) as a tool for collecting, storing, analysing, and disseminating spatial information. The purpose of this paper is to propose the first step of a general framework for presenting the location of confidential point data on maps using empirical perceptual research. The overall objective is to identify geographic masking methods that preserve both the confidentiality of individual locations, and at the same time the essential visual characteristics of the original point pattern.
Key concepts: Confidentiality, Masking (illustration), Computer science, Dissemination, Point (geometry), Perception, Data science, Spatial analysis