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Open Access Highly Accessed Editorial

Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data

Maged N Kamel Boulos1*, Teeradache Viangteeravat2, Matthew N Anyanwu2, Venkateswara Ra Nagisetty2 and Emin Kuscu2

Author affiliations

1 Faculty of Health, University of Plymouth, Drake Circus, Plymouth, Devon, PL4 8AA, UK

2 Clinical and Translational Science Institute, University of Tennessee Health Science Center, Memphis, TN 38163, USA

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Citation and License

International Journal of Health Geographics 2011, 10:19  doi:10.1186/1476-072X-10-19

Published: 16 March 2011

Abstract

The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable aspects. This paper introduces geospatial visual analytics, a specialised subtype of visual analytics, and provides pointers to a number of learning resources about the subject, as well as some examples of human health, surveillance, emergency management and epidemiology-related geospatial visual analytics applications and examples of free software tools that readers can experiment with, such as Google Public Data Explorer. The authors also present a practical demonstration of geospatial visual analytics using partial data for 35 countries from a publicly available World Health Organization (WHO) mortality dataset and Microsoft Live Labs Pivot technology, a free, general purpose visual analytics tool that offers a fresh way to visually browse and arrange massive amounts of data and images online and also supports geographic and temporal classifications of datasets featuring geospatial and temporal components. Interested readers can download a Zip archive (included with the manuscript as an additional file) containing all files, modules and library functions used to deploy the WHO mortality data Pivot collection described in this paper.