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Multi-source dataset for urban computing in a Smart City
It is vital to capture and analyze, from various sources in smart cities, the data that are beneficial in urban planning and decision making for governments and individuals. Urban policy makers can find a suitable solution for urban development by using the opportunities and capacities of big data,...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302253/ https://www.ncbi.nlm.nih.gov/pubmed/30581931 http://dx.doi.org/10.1016/j.dib.2018.09.113 |
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author | Honarvar, Ali Reza Sami, Ashkan |
author_facet | Honarvar, Ali Reza Sami, Ashkan |
author_sort | Honarvar, Ali Reza |
collection | PubMed |
description | It is vital to capture and analyze, from various sources in smart cities, the data that are beneficial in urban planning and decision making for governments and individuals. Urban policy makers can find a suitable solution for urban development by using the opportunities and capacities of big data, and by combining different heterogeneous data resources in smart cities. This paper presents data related to urban computing with an aim of assessing the knowledge that can be obtained through integration of multiple independent data sources in Smart Cities. The data contains multiple sources in the city of Aarhus, Denmark from August 1, 2014 to September 30, 2014. The sources include land use, waterways, water barriers, buildings, roads, amenities, POI, weather, traffic, pollution, and parking lot data. The published data in this paper is an extended version of the City Pulse project data to which additional data sources collected from online sources have been added. |
format | Online Article Text |
id | pubmed-6302253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-63022532018-12-21 Multi-source dataset for urban computing in a Smart City Honarvar, Ali Reza Sami, Ashkan Data Brief Computer Science It is vital to capture and analyze, from various sources in smart cities, the data that are beneficial in urban planning and decision making for governments and individuals. Urban policy makers can find a suitable solution for urban development by using the opportunities and capacities of big data, and by combining different heterogeneous data resources in smart cities. This paper presents data related to urban computing with an aim of assessing the knowledge that can be obtained through integration of multiple independent data sources in Smart Cities. The data contains multiple sources in the city of Aarhus, Denmark from August 1, 2014 to September 30, 2014. The sources include land use, waterways, water barriers, buildings, roads, amenities, POI, weather, traffic, pollution, and parking lot data. The published data in this paper is an extended version of the City Pulse project data to which additional data sources collected from online sources have been added. Elsevier 2018-10-03 /pmc/articles/PMC6302253/ /pubmed/30581931 http://dx.doi.org/10.1016/j.dib.2018.09.113 Text en © 2018 Published by Elsevier Inc. http://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 | Computer Science Honarvar, Ali Reza Sami, Ashkan Multi-source dataset for urban computing in a Smart City |
title | Multi-source dataset for urban computing in a Smart City |
title_full | Multi-source dataset for urban computing in a Smart City |
title_fullStr | Multi-source dataset for urban computing in a Smart City |
title_full_unstemmed | Multi-source dataset for urban computing in a Smart City |
title_short | Multi-source dataset for urban computing in a Smart City |
title_sort | multi-source dataset for urban computing in a smart city |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6302253/ https://www.ncbi.nlm.nih.gov/pubmed/30581931 http://dx.doi.org/10.1016/j.dib.2018.09.113 |
work_keys_str_mv | AT honarvaralireza multisourcedatasetforurbancomputinginasmartcity AT samiashkan multisourcedatasetforurbancomputinginasmartcity |