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== Abstract == | == Abstract == | ||
| − | Number of studies covering major data aspects of OpenStreetMap (OSM) for developed cities and countries are available in scientific literature. However, this is not the case for developing ones mainly because of low data availability in OSM. This study presents a time-series spatial analysis of Turkey OSM dataset, a developing country, between the year 2007 and 2015 to understand how the dataset has developed with time and space. Five different socio-economic factors of the region are tested to find their relationship, if any, with dataset growth. An east-west spatial trend in data density is observed within the country. | + | Number of studies covering major data aspects of OpenStreetMap (OSM) for developed cities and countries are available in scientific literature. However, this is not the case for developing ones mainly because of low data availability in OSM. This study presents a time-series spatial analysis of Turkey OSM dataset, a developing country, between the year 2007 and 2015 to understand how the dataset has developed with time and space. Five different socio-economic factors of the region are tested to find their relationship, if any, with dataset growth. An east-west spatial trend in data density is observed within the country. ''Population Density'' and ''Literacy Level'' of the region are found be the factors controlling it. It has also been observed that the street network of the region has followed the Exploration and Densification evolutionary model. High participation inequality is found within the OSM mappers, with only 5 of them responsible for the country’s 50% geo-data upload. Furthermore, it is found that these mappers use other Volunteered Geographic Information (VGI) and government open-dataset to feed into OSM. This study is believed to bring some high level insights of OSM for a developing country which would be useful for geographers, open-data policy makers, VGI projects planners and data-curators to structure and deploy similar future projects. |
Document type: Article | Document type: Article | ||
Latest revision as of 14:54, 5 March 2021
Abstract
Number of studies covering major data aspects of OpenStreetMap (OSM) for developed cities and countries are available in scientific literature. However, this is not the case for developing ones mainly because of low data availability in OSM. This study presents a time-series spatial analysis of Turkey OSM dataset, a developing country, between the year 2007 and 2015 to understand how the dataset has developed with time and space. Five different socio-economic factors of the region are tested to find their relationship, if any, with dataset growth. An east-west spatial trend in data density is observed within the country. Population Density and Literacy Level of the region are found be the factors controlling it. It has also been observed that the street network of the region has followed the Exploration and Densification evolutionary model. High participation inequality is found within the OSM mappers, with only 5 of them responsible for the country’s 50% geo-data upload. Furthermore, it is found that these mappers use other Volunteered Geographic Information (VGI) and government open-dataset to feed into OSM. This study is believed to bring some high level insights of OSM for a developing country which would be useful for geographers, open-data policy makers, VGI projects planners and data-curators to structure and deploy similar future projects.
Document type: Article
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Original document
The different versions of the original document can be found in:
- https://www.degruyter.com/downloadpdf/journals/geo/11/1/article-p140.pdf under the license https://creativecommons.org/licenses/by
- http://www.degruyter.com/view/j/geo.2019.11.issue-1/geo-2019-0012/geo-2019-0012.pdf,
- http://dx.doi.org/10.1515/geo-2019-0012 under the license cc-by
- https://doaj.org/toc/2391-5447 under the license http://creativecommons.org/licenses/by/4.0
- https://ui.adsabs.harvard.edu/abs/2019OGeo...11...12Z/abstract,
- https://academic.microsoft.com/#/detail/2940206239
- [ ]
Document information
Published on 31/03/19
Accepted on 31/03/19
Submitted on 31/03/19
Volume 2019, 2019
DOI: 10.1515/geo-2019-0012
Licence: CC BY-NC-SA license
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