Open Data for web-mapping the dynamic of population of Uzbekistan

DOI: 10.35595/2414-9179-2021-4-27-388-401

Посмотреть или загрузить статью (Eng)

Об авторах

Lola X. Gulyamova

Tashkent State Technical University,
Universitetskaya str. 2, 10074, Tashkent, Uzbekistan;

Dilshod N. Rakhmonov

National Unversity of Uzbekistan,
Universitetskaya str. 4, 10074, Tashkent, Uzbekistan;


This paper covers issues related to using Open Data for web mapping of the dynamic of population of Uzbekistan. Several ways are suggested for performing an analysis of patterns of dynamic of population. The web mapping is recommended as the preferable way for study the spatial distribution of the population and its change. The methods are described from the perspective of their relevance to the technical and conceptual development of interactive dynamic maps. The Open sources that are maintained by state agencies, committees, private companies and other institutions are used for web mapping. The peculiarities of development of Open Data in this country are analyzed with the purpose of applying geoinformation technologies for capturing geospatial information (GI). The model has been developed for using web mapping tools for combining ICT, GIS, interactive cartography and socio-economic data for retrieving GI from existing open resources. Some tools are suggested to bring together Open Data of different official sources by means of Geographical Information Systems. The model of web service is used for uploading map data to a cloud account, while cloud service handles all server-side. ArcGIS Online and other open software are applied for interactive mapping. The interaction with datasets for online mapping and spatial analysis is performed with the help of the cloud service of ArcGIS Online.

Ключ. слова

open data, web mapping, population, dynamics, Uzbekistan

Список литературы

  1. Baturin Y., Dmitrieva V., Eremchenko E., Massel L., Nikonov O., Romanov A., Tikunov V., Zakharova A. et al. Digital Earth in Russia. In: Guo H., Goodchild M.F., Annoni A. (eds) Manual of Digital Earth. Springer, Singapore. 2020. P. 733–752. DOI: 10.1007/978-981-32-9915-3_23.
  2. Charalabidis Y., Loukis E., Alexopoulos C. Evaluating Second Generation Open Government Data Infrastructures Using Value Models. In Proceedings of the 2014 47th Hawaii International Conference on System Sciences, Waikoloa, HI, USA, 6–9 January 2014. P. 2114–2126.
  3. Davies T., Walker S.B., Rubinstein M. Perini F. The State of Open Data: Histories and Horizons. 2019. Publisher African Minds, IDRC (accessed on July 31, 2021
  4. Dmowska A. Dasymetric Modelling of Population Distribution—Large Data Approach. Quaestiones Geographicae, 2019. V. 38. No. 1. P. 15–27. DOI: 10.2478/quageo-2019-0008.
  5. Eremchenko E., Tikunov V., Ivanov R., Massel L., Strobl J. Digital Earth and Evolution of Cartography. Procedia Computer Science. 2015. V. 66. P. 235–238.
  6. Goodchild M. Citizens as Sensors: The World of Volunteered Geography. GeoJournal 2007. No. 69 (4). P. 211-221 DOI: 10.1007/s10708-007-9111-y.
  7. Goodchild M., Li L. Assuring the Quality of Volunteered Geographic Information. Spatial Statistics. 2012. No. 1. P. 110–120. DOI: 10.1016/j.spasta.2012.03.002.
  8. Goodchild M., Li W. Replication across space and time must be weak in the social and environmental sciences. Proceedings of the National Academy of Sciences of the United States of America. PNAS August 31, 2021. No. 118 (35) e2015759118. DOI: 10.1073/pnas.2015759118.
  9. Gulyamova L. Geographical Information Systems and Technologies. Tashkent, “University”, 2018. 188 p. (in Uzbek).
  10. Kerski J. 10 Ways to Study Demographics with Web GIS. ESRI. March 2020. Web resource (accessed 12.05.2021).
  11. Mooney P., Minghini M. Review of OpenStreetMap Data. Mapping and the Citizen Sensor. 2017. P. 37–59. London: Ubiquity Press. DOI: 10.5334/bbf.c. (accessed on August 19, 2021).
  12. Quarati A., De Martino M., Rosim S. Geospatial Open Data Usage and Metadata Quality. ISPRS Int. J. Geo-Inf. 2021, 10, 30. DOI: 10.3390/ijgi10010030 (accessed Aug 21 2021).
  13. Roth R. Cartographic interaction primitives: Framework and synthesis. The Cartographic Journal. 2013. 49 (4). P. 376–395. DOI: 10/1179/1743277412Y.00000000019.
  14. Smith D. Online interactive thematic mapping: Applications and techniques for socio-economic research. Computers, Environment and Urban Systems. 2016. 57. P. 106–117. DOI: 10/1016/j.compenvurbsys.2018.01.002.
  15. Verhulst S., Young A. Open Data in Developing Economies. Toward Building an Evidence Base on What Works and How. 2017. Published by African Minds.
  16. Viscusi G., Castelli M., Batini C. Assessing social value in open data initiatives: A framework. Future Internet. 2014. No. 6. P. 498–517.
  17. Zastrow M. Data visualization: Science on the map. Nature. 2015. V. 519 (7541). P. 119–120. DOI: 10/1038/519119a.

Для цитирования: Gulyamova L.X., Rakhmonov D.N. Open Data for web-mapping the dynamic of population of Uzbekistan. ИнтерКарто. ИнтерГИС. Геоинформационное обеспечение устойчивого развития территорий: Материалы Междунар. конф. M: Географический факультет МГУ, 2021. Т. 27. Ч. 4. С. 388–401 DOI: 10.35595/2414-9179-2021-4-27-388-401

For citation: Gulyamova L.X., Rakhmonov D.N. Open Data for web-mapping the dynamic of population of Uzbekistan. InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: MSU, Faculty of Geography, 2021. V. 27. Part 4. P. 388–401. DOI: 10.35595/2414-9179-2021-4-27-388-401