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Visualizing multiple variables across scale and geography

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Goodwin, Sarah, Dykes, Jason, Slingsby, Aidan and Turkay, Cagatay (2016) Visualizing multiple variables across scale and geography. IEEE Transactions on Visualization and Computer Graphics, 22 (1). pp. 599-608. doi:10.1109/TVCG.2015.2467199

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Official URL: http://dx.doi.org/10.1109/TVCG.2015.2467199

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Abstract

Comparing multiple variables to select those that effectively characterize complex entities is important in a wide variety of domains - geodemographics for example. Identifying variables that correlate is a common practice to remove redundancy, but correlation varies across space, with scale and over time, and the frequently used global statistics hide potentially important differentiating local variation. For more comprehensive and robust insights into multivariate relations, these local correlations need to be assessed through various means of defining locality. We explore the geography of this issue, and use novel interactive visualization to identify interdependencies in multivariate data sets to support geographically informed multivariate analysis. We offer terminology for considering scale and locality, visual techniques for establishing the effects of scale on correlation and a theoretical framework through which variation in geographic correlation with scale and locality are addressed explicitly. Prototype software demonstrates how these contributions act together. These techniques enable multiple variables and their geographic characteristics to be considered concurrently as we extend visual parameter space analysis (vPSA) to the spatial domain. We find variable correlations to be sensitive to scale and geography to varying degrees in the context of energy-based geodemographics. This sensitivity depends upon the calculation of locality as well as the geographical and statistical structure of the variable.

Item Type: Journal Article
Divisions: Faculty of Social Sciences > Centre for Interdisciplinary Methodologies
Journal or Publication Title: IEEE Transactions on Visualization and Computer Graphics
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 1077-2626
Official Date: 2016
Dates:
DateEvent
2016Published
12 July 2015Accepted
Volume: 22
Number: 1
Page Range: pp. 599-608
DOI: 10.1109/TVCG.2015.2467199
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
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