Geofaceting: Aligning small-multiples for regions in a spatially meaningful way

<b>Background</b>: Creating visualizations that include multiple dimensions of the data while preserving spatial structure and readability is challenging. Here we demonstrate the use of geofaceting to meet this challenge. <b>Objective</b>: Using data on young adult mortali...

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Main Authors: Ilya Kashnitsky, José Manuel Aburto
Format: Article
Language:English
Published: Max Planck Institute for Demographic Research 2019-08-01
Series:Demographic Research
Online Access:https://www.demographic-research.org/volumes/vol41/17/
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spelling doaj-a282a339e63d4f50904cc73f5cabee1f2020-11-25T03:42:24ZengMax Planck Institute for Demographic ResearchDemographic Research1435-98712019-08-01411710.4054/DemRes.2019.41.174424Geofaceting: Aligning small-multiples for regions in a spatially meaningful wayIlya Kashnitsky0José Manuel Aburto1Syddansk UniversitetUniversity of Oxford<b>Background</b>: Creating visualizations that include multiple dimensions of the data while preserving spatial structure and readability is challenging. Here we demonstrate the use of geofaceting to meet this challenge. <b>Objective</b>: Using data on young adult mortality in the 32 Mexican states from 1990 to 2015, we demonstrate how aligning small multiples for territorial units, often regions, according to their approximate geographical location - geofaceting - can be used to depict complex multi-dimensional phenomena. <b>Methods</b>: The idea is to align small-multiples for territorial units, often regions, according to approximate geographical location. We illustrate the technique using data on young adult mortality in the 32 Mexican states from 1990 to 2015. <b>Results</b>: Geofaceting reveals the macro-level spatial pattern while preserving the flexibility of choosing any visualization techniques for the small multiples. Creating geofaceted visualizations gives all the advantages of standard plots in which one can adequately display multiple dimensions of a dataset. <b>Contribution</b>: Compared to other ways of small-multiples' arrangement, geofaceting improves the speed of regions' identification and exposes the broad spatial pattern.https://www.demographic-research.org/volumes/vol41/17/
collection DOAJ
language English
format Article
sources DOAJ
author Ilya Kashnitsky
José Manuel Aburto
spellingShingle Ilya Kashnitsky
José Manuel Aburto
Geofaceting: Aligning small-multiples for regions in a spatially meaningful way
Demographic Research
author_facet Ilya Kashnitsky
José Manuel Aburto
author_sort Ilya Kashnitsky
title Geofaceting: Aligning small-multiples for regions in a spatially meaningful way
title_short Geofaceting: Aligning small-multiples for regions in a spatially meaningful way
title_full Geofaceting: Aligning small-multiples for regions in a spatially meaningful way
title_fullStr Geofaceting: Aligning small-multiples for regions in a spatially meaningful way
title_full_unstemmed Geofaceting: Aligning small-multiples for regions in a spatially meaningful way
title_sort geofaceting: aligning small-multiples for regions in a spatially meaningful way
publisher Max Planck Institute for Demographic Research
series Demographic Research
issn 1435-9871
publishDate 2019-08-01
description <b>Background</b>: Creating visualizations that include multiple dimensions of the data while preserving spatial structure and readability is challenging. Here we demonstrate the use of geofaceting to meet this challenge. <b>Objective</b>: Using data on young adult mortality in the 32 Mexican states from 1990 to 2015, we demonstrate how aligning small multiples for territorial units, often regions, according to their approximate geographical location - geofaceting - can be used to depict complex multi-dimensional phenomena. <b>Methods</b>: The idea is to align small-multiples for territorial units, often regions, according to approximate geographical location. We illustrate the technique using data on young adult mortality in the 32 Mexican states from 1990 to 2015. <b>Results</b>: Geofaceting reveals the macro-level spatial pattern while preserving the flexibility of choosing any visualization techniques for the small multiples. Creating geofaceted visualizations gives all the advantages of standard plots in which one can adequately display multiple dimensions of a dataset. <b>Contribution</b>: Compared to other ways of small-multiples' arrangement, geofaceting improves the speed of regions' identification and exposes the broad spatial pattern.
url https://www.demographic-research.org/volumes/vol41/17/
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AT josemanuelaburto geofacetingaligningsmallmultiplesforregionsinaspatiallymeaningfulway
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