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A standardized European hexagon gridded dataset based on OpenStreetMap POIs

Point of interest (POI) data refers to information about the location and type of amenities, services, and attractions within a geographic area. This data is used in urban studies research to better understand the dynamics of a city, assess community needs, and identify opportunities for economic gr...

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Detalles Bibliográficos
Autores principales: McCarty, Dakota Aaron, Kim, Hyun Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439266/
https://www.ncbi.nlm.nih.gov/pubmed/37600132
http://dx.doi.org/10.1016/j.dib.2023.109315
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author McCarty, Dakota Aaron
Kim, Hyun Woo
author_facet McCarty, Dakota Aaron
Kim, Hyun Woo
author_sort McCarty, Dakota Aaron
collection PubMed
description Point of interest (POI) data refers to information about the location and type of amenities, services, and attractions within a geographic area. This data is used in urban studies research to better understand the dynamics of a city, assess community needs, and identify opportunities for economic growth and development. POI data is beneficial because it provides a detailed picture of the resources available in a given area, which can inform policy decisions and improve the quality of life for residents. This paper presents a large-scale, standardized POI dataset from OpenStreetMap (OSM) for the European continent. The dataset's standardization and gridding make it more efficient for advanced modeling, reducing 7,218,304 data points to 988,575 without significant resolution loss, suitable for a broader range of models with lower computational demands. The resulting dataset can be used to conduct advanced analyses, examine POI spatial distributions, conduct comparative regional studies, and research to help enhance the understanding of the distribution of economic activity and attractions, and subsequently help in the understanding of the economic health, growth potential, and cultural opportunities of an area. The paper describes the materials and methods used in generating the dataset, including OSM data retrieval, processing, standardization, hexagonal grid generation, and point count aggregations. The dataset can be used independently or integrated with other relevant datasets for more comprehensive spatial distribution studies in future research.
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spelling pubmed-104392662023-08-20 A standardized European hexagon gridded dataset based on OpenStreetMap POIs McCarty, Dakota Aaron Kim, Hyun Woo Data Brief Data Article Point of interest (POI) data refers to information about the location and type of amenities, services, and attractions within a geographic area. This data is used in urban studies research to better understand the dynamics of a city, assess community needs, and identify opportunities for economic growth and development. POI data is beneficial because it provides a detailed picture of the resources available in a given area, which can inform policy decisions and improve the quality of life for residents. This paper presents a large-scale, standardized POI dataset from OpenStreetMap (OSM) for the European continent. The dataset's standardization and gridding make it more efficient for advanced modeling, reducing 7,218,304 data points to 988,575 without significant resolution loss, suitable for a broader range of models with lower computational demands. The resulting dataset can be used to conduct advanced analyses, examine POI spatial distributions, conduct comparative regional studies, and research to help enhance the understanding of the distribution of economic activity and attractions, and subsequently help in the understanding of the economic health, growth potential, and cultural opportunities of an area. The paper describes the materials and methods used in generating the dataset, including OSM data retrieval, processing, standardization, hexagonal grid generation, and point count aggregations. The dataset can be used independently or integrated with other relevant datasets for more comprehensive spatial distribution studies in future research. Elsevier 2023-06-14 /pmc/articles/PMC10439266/ /pubmed/37600132 http://dx.doi.org/10.1016/j.dib.2023.109315 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
McCarty, Dakota Aaron
Kim, Hyun Woo
A standardized European hexagon gridded dataset based on OpenStreetMap POIs
title A standardized European hexagon gridded dataset based on OpenStreetMap POIs
title_full A standardized European hexagon gridded dataset based on OpenStreetMap POIs
title_fullStr A standardized European hexagon gridded dataset based on OpenStreetMap POIs
title_full_unstemmed A standardized European hexagon gridded dataset based on OpenStreetMap POIs
title_short A standardized European hexagon gridded dataset based on OpenStreetMap POIs
title_sort standardized european hexagon gridded dataset based on openstreetmap pois
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439266/
https://www.ncbi.nlm.nih.gov/pubmed/37600132
http://dx.doi.org/10.1016/j.dib.2023.109315
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