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The Use of Geonarratives to Add Context to Fine Scale Geospatial Research
There has been a move towards using mixed method approaches in geospatial research to gain context in understanding health related social patterns and processes. The central premise is that official data is often too reductionist and misses’ nuances that can help explain causality. One example is th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388256/ https://www.ncbi.nlm.nih.gov/pubmed/30759776 http://dx.doi.org/10.3390/ijerph16030515 |
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author | Ajayakumar, Jayakrishnan Curtis, Andrew Smith, Steve Curtis, Jacqueline |
author_facet | Ajayakumar, Jayakrishnan Curtis, Andrew Smith, Steve Curtis, Jacqueline |
author_sort | Ajayakumar, Jayakrishnan |
collection | PubMed |
description | There has been a move towards using mixed method approaches in geospatial research to gain context in understanding health related social patterns and processes. The central premise is that official data is often too reductionist and misses’ nuances that can help explain causality. One example is the geonarrative, a spatially relevant commentary or interview that can be mapped by content and/or location. While there have been several examples of geonarratives being used by researchers, there is no commonly available software that can easily transfer the associated text into spatial data. Having a standardized software platform is vital if these methods are to be used across different disciplines. This paper presents an overview of a solution, Wordmapper (WM), which is a standalone software developed to process geonarratives from a transcription and associated global positioning system (GPS) path. Apart from querying textual narrative data, Wordmapper facilitates qualitative coding which could be used to extract latent contextual information from the narratives. In order to improve interoperability, Wordmapper provides spatialized narrative data in formats, such as ESRI shape files, Keyhole Markup Language (KML), and Comma Separated Values (CSV). A case study based on five different spatial video geonarratives (SVG) collected to assess the human impacts following the 2011 Joplin, Missouri are used for illustration. |
format | Online Article Text |
id | pubmed-6388256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63882562019-02-27 The Use of Geonarratives to Add Context to Fine Scale Geospatial Research Ajayakumar, Jayakrishnan Curtis, Andrew Smith, Steve Curtis, Jacqueline Int J Environ Res Public Health Article There has been a move towards using mixed method approaches in geospatial research to gain context in understanding health related social patterns and processes. The central premise is that official data is often too reductionist and misses’ nuances that can help explain causality. One example is the geonarrative, a spatially relevant commentary or interview that can be mapped by content and/or location. While there have been several examples of geonarratives being used by researchers, there is no commonly available software that can easily transfer the associated text into spatial data. Having a standardized software platform is vital if these methods are to be used across different disciplines. This paper presents an overview of a solution, Wordmapper (WM), which is a standalone software developed to process geonarratives from a transcription and associated global positioning system (GPS) path. Apart from querying textual narrative data, Wordmapper facilitates qualitative coding which could be used to extract latent contextual information from the narratives. In order to improve interoperability, Wordmapper provides spatialized narrative data in formats, such as ESRI shape files, Keyhole Markup Language (KML), and Comma Separated Values (CSV). A case study based on five different spatial video geonarratives (SVG) collected to assess the human impacts following the 2011 Joplin, Missouri are used for illustration. MDPI 2019-02-12 2019-02 /pmc/articles/PMC6388256/ /pubmed/30759776 http://dx.doi.org/10.3390/ijerph16030515 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ajayakumar, Jayakrishnan Curtis, Andrew Smith, Steve Curtis, Jacqueline The Use of Geonarratives to Add Context to Fine Scale Geospatial Research |
title | The Use of Geonarratives to Add Context to Fine Scale Geospatial Research |
title_full | The Use of Geonarratives to Add Context to Fine Scale Geospatial Research |
title_fullStr | The Use of Geonarratives to Add Context to Fine Scale Geospatial Research |
title_full_unstemmed | The Use of Geonarratives to Add Context to Fine Scale Geospatial Research |
title_short | The Use of Geonarratives to Add Context to Fine Scale Geospatial Research |
title_sort | use of geonarratives to add context to fine scale geospatial research |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388256/ https://www.ncbi.nlm.nih.gov/pubmed/30759776 http://dx.doi.org/10.3390/ijerph16030515 |
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