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Improving Volunteered Geographic Information Quality Using a Tag Recommender System: The Case of OpenStreetMap

  • Arnaud Vandecasteele
  • Rodolphe Devillers
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Studies have analyzed the quality of volunteered geographic information (VGI) datasets, assessing the positional accuracy of features and the semantic accuracy of the attributes. While it has been shown that VGI can, in some contexts, reach a high positional accuracy, these studies have also highlighted a large spatial heterogeneity in positional accuracy and completeness, but also concerning the semantics of the objects. Such high semantic heterogeneity of VGI datasets becomes a significant obstacle to a number of possible uses that could be made of the data. This paper proposes an approach for both improving the semantic quality and reducing the semantic heterogeneity of VGI datasets. The improvement of the semantic quality is achieved by using a tag recommender system, called OSMantic, which automatically suggests relevant tags to contributors during the editing process. Such an approach helps contributors find the most appropriate tags for a given object, hence reducing the overall dataset semantic heterogeneity. The approach was implemented into a plugin for the Java OpenStreetMap editor (JOSM) and different examples illustrate how this plugin can be used to improve the quality of VGI data. This plugin has been tested by OSM contributors and evaluated using an online questionnaire. Results of the evaluation suggest a high level of satisfaction from users and are discussed.

Keywords

Volunteered geographic information (VGI) Semantic similarity Data quality OpenStreetMap (OSM) 

Notes

Acknowledgments

This research was funded by the Natural Science and Engineering Research Council of Canada (NSERC) through the second author’s NSERC Discovery Accelerator Supplement Program. Authors also thank Dr. Andrea Ballatore for sharing his results, Vincent Privat for his helpful feedback on JOSM, Daniel Bégin for his early tests of the plugin and the 30 OSM contributors that participated in the evaluation of the plugin.

References

  1. Auer S, Lehmann J, Hellmann S (2009) LinkedGeoData: adding a spatial dimension to the web of data. In: Proceedings of the 8th international semantic web conference, ISWC’09, Washington, DC. Lecture notes in computer science, vol 5823, Springer, Berlin, pp 731–746Google Scholar
  2. Ballatore A, Bertolotto M, Wilson DC (2013) Geographic knowledge extraction and semantic similarity in OpenStreetMap. Knowl Inf Syst (KAIS) 37(1):61–81CrossRefGoogle Scholar
  3. Barron C, Neis P, Zipf A (2014) A comprehensive framework for intrinsic OpenStreetMap quality analysis. Trans GIS 18(6):877−895. doi: 10.1111/tgis.12073
  4. Bégin D, Devillers R, Roche S (2013) Assessing volunteered geographic information (VGI) quality based on contributors’ mapping behaviours. In: Proceedings of the 8th international symposium on spatial data quality ISSDQ 2013, Hong Kong, China, pp 149–154Google Scholar
  5. Bland JM, Altman DG (1997) Statistics notes: Cronbach’s alpha. BMJ 314:572Google Scholar
  6. Budhathoki NR, Nedović-Budić Z, Bertram B (2010) An interdisciplinary frame for understanding volunteered geographic information. J Geospat Inf Sci Technol Pract 64(1):11–26Google Scholar
  7. Codescu M, Horsinka G, Kutz O, Mossakowski T, Rau R (2011) DO-ROAM: activity-oriented search and navigation with OpenStreetMap. In: Claramunt C, Levashkin S, Bertolotto M (eds) Fourth international conference on geospatial semantics, vol 6631, Brest, France. Lecture notes in computer science, Springer, Berlin, pp 88–107Google Scholar
  8. Coleman DJ, Georgiadou Y, Labonte J (2009) Volunteered geographic information: the nature and motivation of produsers. Int J Spat Data Infrastruct Res 4:332–358Google Scholar
  9. Elwood S, Goodchild MF, Sui DZ (2012) Researching volunteered geographic information: spatial data, geographic research, and new social practice. Ann Assoc Am Geogr 103(3):571–590CrossRefGoogle Scholar
  10. Flanagin AJ, Metzger MJ (2008) The credibility of volunteered geographic information. GeoJournal 72:137–148Google Scholar
  11. Girres J-F, Touya G (2010) Quality assessment of the French OpenStreetMap dataset. Trans GIS 14(4):435–459CrossRefGoogle Scholar
  12. Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. GeoJournal 69:211–221Google Scholar
  13. Goodchild MF, Li L (2012) Assuring the quality of volunteered geographic information. Spat Stat 1:110–120CrossRefGoogle Scholar
  14. Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environ Plann B: Plann Des 37:682–703Google Scholar
  15. Haklay M (2013) Citizen science and volunteered geographic information: overview and typology of participation. In: Sui D, Elwood S, Goodchild M (eds) Crowdsourcing geographic knowledge. Springer, The Netherlands, pp 105–122Google Scholar
  16. Haklay M, Basiouka S, Antoniou V, Ather A (2010) How many volunteers does it take to map an area well? The validity of Linus’ law to volunteered geographic information. Cartographic J 47(4):315–322Google Scholar
  17. ISO/TC 211 (2002) 19113 Geographic information—quality principles. International Organization for Standardization (No. ISO 19113:2002). International Organization for Standardization (ISO)Google Scholar
  18. Keßler C, de Groot RTA (2013) Trust as a proxy measure for the quality of volunteered geographic information in the case of OpenStreetMap. In: Association of geographic information laboratories for Europe. Presented at the Agile 2013, Leuven, Belgium, pp 21–37Google Scholar
  19. Ludwig I, Voss A, Krause-Traudes M (2011) A comparison of the street networks of Navteq and OSM in Germany. In: Geertman S, Reinhardt W, Toppen F (eds) Advancing geoinformation science for a changing world. Lecture notes in geoinformation and cartography. Springer, Berlin, pp 65–84Google Scholar
  20. Mooney P, Corcoran P (2012a) The annotation process in OpenStreetMap. Trans GIS 16(4):561–579CrossRefGoogle Scholar
  21. Mooney P, Corcoran P (2012b) Characteristics of heavily edited objects in OpenStreetMap. Future Internet 4(1):285–305CrossRefGoogle Scholar
  22. Mülligann C, Janowicz K, Ye M, Lee W-C (2011) Analyzing the spatial-semantic interaction of points of interest in volunteered geographic information. In: Egenhofer M, Giudice N, Moratz R, Worboys M (eds) Spatial information theory. Lecture notes in computer science. Springer, Berlin, pp 350–370Google Scholar
  23. Neis P, Zipf A (2012) Analyzing the contributor activity of a volunteered geographic information project—the case of OpenStreetMap. ISPRS Int J Geo-Inf 1(2):146–165CrossRefGoogle Scholar
  24. Peters I, Stock WG (2010) “Power tags” in information retrieval. Libr Hi Tech 28(1):81–93CrossRefGoogle Scholar
  25. Pu P, Chen L, Hu R (2011) A user-centric evaluation framework for recommender systems. In: Proceedings of the 5th ACM conference on recommender systems, RecSys ’11. ACM, New York, USA, pp 157–164Google Scholar
  26. Rehrl K, Gröechenig S, Hochmair H, Leitinger S, Steinmann R, Wagner A (2013) A conceptual model for analyzing contribution patterns in the context of VGI. In: Krisp JM (ed) Progress in location-based services. Lecture notes in geoinformation and cartography. Springer, Berlin, pp 373–388Google Scholar
  27. Smith B, Mark DM (2003) Do mountains exist? Towards an ontology of landforms. Environ Plan 30(3):411–427CrossRefGoogle Scholar
  28. Tobler W (1970) A computer movie simulating urban growth in the detroit region. Econ Geogr 46:234–240CrossRefGoogle Scholar
  29. van Exel M, Dias E (2011) Towards a methodology for trust stratification in VGI. In: Volunteered geographic information (VGI)—research progress and new developments. Presented at the association of American geographers annual meeting 2011, Seattle, Washington, p 4Google Scholar
  30. Zhao P, Han J, Sun Y (2009) PRank: a comprehensive structural similarity measure over information networks. In: Proceedings of the 18th ACM conference in information and knowledge management. Presented at the CIKM, 09, ACM Press, New York, pp 553–562Google Scholar
  31. Zipf GK (1949) Human behavior and the principle of least effort: an introduction to human ecology. Martino fine books, USA. p 588Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of GeographyMemorial University of NewfoundlandSt. John’sCanada

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