A brute force method for spatially-enhanced multivariate facet analysis

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Faceted search is a common approach for helping users query multivariate data. While the method is found widely in contemporary tools, so far there has been little exploration of its potential to incorporate a spatial perspective. In this article we extend multivariate faceted search through the application of a brute force computational process to reveal facet combinations that have spatially-interesting results. We explore the potential utility of spatially-enhanced facet combinations in case study analyses of multivariate spatial data from learners in a massive open online course and multivariate spatial data from restaurant inspections. Spatially-enhanced facet combinations improve on ordinary faceted search by helping analysts understand which combinations have significant spatial footprints. We also show how this method can be integrated into a geovisual analytics system through a simple user interface. Finally, we draw on our case study analyses to highlight important challenges and opportunities for future research.


This article was originally published in Computers, Environment and Urban Systems. The full-text article from the publisher can be found here.

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Computers, Environment and Urban Systems


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