Open Access Open Access  Restricted Access Subscription or Fee Access

A Literature Review on Quality Assurance Mechanisms for Volunteered Geographic Information

Mennatallah H. Ibrahim, Nagy Ramadan Darwish, Hesham A. Hefny

Abstract


Nowadays, Volunteered Geographic Information (VGI) becomes an important source of massive citizen-generated Geographic Information (GI) datasets. VGI not only creates new GI datasets, it enriches the existing authoritative datasets as well. Furthermore, in some contexts where authoritative datasets is not available, VGI may be the only source of GI. Although, VGI possess numerous advantages, it unfortunately faces several challenges. One of the clear challenges that face VGI is the quality. VGI quality is inherently heterogeneous and VGI lacks quality assurance. Due to its different nature, VGI does not comply with standard quality assurance procedures that are applied to spatial data. Thus, assuring VGI quality becomes increasingly important. Various previously proposed studies are concerned with VGI quality assurance. This paper conducts a literature review on previously proposed VGI quality assurance mechanisms. The paper discusses each mechanism and its limitations. A comparison between all proposed mechanisms is conducted as well.


Keywords


Geographic Information Systems, Spatial Data, Volunteered Geographic Information, Quality Assurance, Quality

Full Text:

PDF

References


G. Charest-Hallée, and M. Dube, 2010. "Spatial Information and Volunteering." http://spatial.umaine.edu. (Accessed 05-07-2019).

M. Goodchild, “Citizens as sensors: the world of volunteered geography,” GeoJournal, vol. 69, pp. 211-221. 2007.

D. Hardy, et al. "Volunteered geographic information production as a spatial process." International Journal of Geographical Information Science, vol. 26, pp. 1191-1212. 2012.

C. Seeger, “The role of facilitated volunteered geographic information in the landscape planning and site design process.” GeoJournal, vol 72, pp. 199-213. 2008.

S. Elwood, "Volunteered geographic information: future research directions motivated by critical, participatory, and feminist GIS." GeoJournal 72. vol. 3, pp. 173-183. 2008.

V. Fast, and R. Claus, "A systems perspective on volunteered geographic information." ISPRS International Journal of Geo-Information, vol. 3, pp. 1278-1292. 2014.

L. See, et al. “Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information,” ISPRS International Journal of Geo-Information, vol. 5 .2016.

J. Gómez-Barrón, et al. Volunteered Geographic Information system design: Project and participation guidelines. ISPRS International Journal of Geo-Information, vol. 5, pp. 108. 2016.

A. Ballatore, and A. Zipf, “A conceptual quality framework for Volunteered Geographic Information”. In International Conference on Spatial Information Theory, Springer, Cham, pp. 89-107, 2015.

M. Haklay, et al. “How many volunteers does it take to map an area well? The validity of Linus’ law to volunteered geographic information,” The Cartographic Journal, vol. 47, pp. 315-322. 2010.

G. Foody, et al. “Accurate attribute mapping from volunteered geographic information: issues of volunteer quantity and quality,” The Cartographic Journal, vol. 52, pp. 336-344. 2015.

Ingensand, J. et al. "Challenges in VGI for scientific projects." PeerJ Preprints 4: e1992v1. 2016.

C. Fonte, et al. Assessing VGI data quality. Mapping and the citizen sensor, PP. 137-163. 2017.

H. Zhang, and J. Malczewski, “Quality Evaluation of Volunteered Geographic Information: The Case of OpenStreetMap,” Volunteered Geographic Information and the Future of Geospatial Data, pp. 19-46. 2017.

J. Meier, “An Analysis of Quality for Volunteered Geographic Information,” thesis, Wilfrid Laurier University, Waterloo, Canada, 2015.

M. Haklay, “How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets,” Environment and planning B: Planning and design, vol. 37, pp. 682-703. 2010.

M. Eshghi, and A. Alesheikh, “Assessment of completeness and positional accuracy of linear features in Volunteered Geographic Information (VGI),” in International Conference on Sensors & Models in Remote Sensing & Photogrammetry, pp. 169, 2015.

Aamer Ather, "A Quality Analysis of OpenStreetMap Data", University College London, 2009.

J. Girres, and G. Touya, “Quality assessment of the French OpenStreetMap dataset,” Transactions in GIS, vol. 14, pp. 435-459.‏ 2010.

A. Ali, et al. “Ambiguity and plausibility: managing classification quality in volunteered geographic information.” In Proceedings of the 22nd ACM SIGSPATIAL international conference on advances in geographic information systems, ACM, pp. 143-152. 2014.

M. Van Exel, et al. “The impact of crowdsourcing on spatial data quality indicators,” in Proc. of the GIScience, pp. 14. 2010

L. Criscuolo, et al.. “Handling quality in crowdsourced geographic information,” European Handbook of Crowdsourced Geographic Information. London: Ubiquity Press, 2016.

D. Fairbairn, and M. Al-Bakri, “Using geometric properties to evaluate possible integration of authoritative and volunteered geographic information,” ISPRS International Journal of Geo-information, vol. 2, pp. 349-370. 2013.

M. Goodchild, and L. Li, “Assuring the quality of volunteered geographic information,” Spatial statistics, vol. 1, pp. 110-120, 2012.

V. Antoniu, “Volunteered geographic information measuring quality, understanding the value,” GEOmedia, vol. 20, pp. 38-45, 2016.

M. Haklay, "Volunteered Geographic Information: Quality Assurance," International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology, pp. 1-6, 2016.

R. Esmaili, et a. “Quality assessment of volunteered geographic information.” Am. J. Geogr. Inf. Syst, vol.2, pp 19-26. 2013.

H. Vahidi, et al. “A fuzzy system for quality assurance of crowdsourced wildlife observation geodata,” In IEEE 2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC) , P. 55. 2017.

L. See, et al. “Comparing the quality of crowdsourced data contributed by expert and non-experts,” PloS one, vol. 8. 2013.

S. Ghosh, et al. “Crowdsourcing for rapid damage assessment: The global earth observation catastrophe assessment network (GEO-CAN),” Earthquake Spectra, vol. 27, pp. 179-198. 2011.

M. Schwind., et al. “Analyzing volunteer geographic information accuracy and determining its capabilities for scientific research data,” Honors and Undergraduate Research. 2014. Available electronically from http: / /hdl .handle .net /1969 .1 /152055.

M. Eckle, and P. de Albuquerque, “Quality assessment of remote mapping in OpenStreetMap for disaster management purposes,” in ISCRAM conference. 2015.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.