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Data Quality Assurance for Volunteered Geographic Information

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Book cover Geographic Information Science (GIScience 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8728))

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Abstract

The availability of technology and tools enables the public to participate in the collection, contribution, editing, and usage of geographic information, a domain previously reserved for mapping agencies or companies. The data of Volunteered Geographic Information (VGI) systems, such as OpenStreetMap (OSM), is based on the availability of technology and participation of individuals. However, this combination also implies quality issues related to the data: some of the contributed entities can be assigned to wrong or implausible classes, due to individual interpretation of the submitted data, or due to misunderstanding about available classes. In this paper we propose two methods to check the integrity of VGI data with respect to hierarchical consistency and classification plausibility. These methods are based on constraint checking and machine learning methods. They can be used to check the validity of data during contribution or at a later stage for collaborative manual or automatic data correction.

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References

  1. Goodchild, M.F.: Citizens as sensors: the world of volunteered geography. GeoJournal 69(4), 211–221 (2007)

    Article  Google Scholar 

  2. Coleman, D.J., Georgiadou, Y., Labonte, J., et al.: Volunteered geographic information: the nature and motivation of produsers. International Journal of Spatial Data Infrastructures Research 4(1), 332–358 (2009)

    Google Scholar 

  3. Feick, R., Roche, S.: Valuing volunteered geographic information (VGI): Opportunities and challenges arising from a new mode of GI use and production. In: Proceedings of the 2nd GEOValue Workshop, HafenCity University Hamburg, Germany, pp. 75–79 (2010)

    Google Scholar 

  4. Zook, M., Graham, M., Shelton, T., Gorman, S.: Volunteered geographic information and crowdsourcing disaster relief: a case study of the Haitian earthquake. World Medical & Health Policy 2(2), 7–33 (2010)

    Article  Google Scholar 

  5. Girres, J.F., Touya, G.: Quality assessment of the french OpenStreetMap dataset. Transactions in GIS 14(4), 435–459 (2010)

    Article  Google Scholar 

  6. Ludwig, I., Voss, A., Krause-Traudes, M.: A comparison of the street networks of Navteq and OSM in Germany. In: Advancing Geoinformation Science for a Changing World, pp. 65–84. Springer (2011)

    Google Scholar 

  7. Neis, P., Zielstra, D., Zipf, A.: The street network evolution of crowdsourced maps: OpenStreetMap in Germany 2007–2011. Future Internet 4(1), 1–21 (2011)

    Article  Google Scholar 

  8. Goodchild, M.F., Li, L.: Assuring the quality of volunteered geographic information. Spatial Statistics 1, 110–120 (2012)

    Article  Google Scholar 

  9. Haklay, M.: How good is volunteered geographical information? a comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning. B, Planning & Design 37(4), 682 (2010)

    Article  Google Scholar 

  10. Neis, P., Zielstra, D., Zipf, A.: Comparison of volunteered geographic information data contributions and community development for selected world regions. Future Internet 5(2), 282–300 (2013)

    Article  Google Scholar 

  11. Mooney, P., Corcoran, P.: The annotation process in OpenStreetMap. Transactions in GIS 16(4), 561–579 (2012)

    Article  Google Scholar 

  12. Elwood, S., Goodchild, M.F., Sui, D.Z.: Researching volunteered geographic information: Spatial data, geographic research, and new social practice. Annals of the Association of American Geographers 102(3), 571–590 (2012)

    Article  Google Scholar 

  13. Mülligann, C., Janowicz, K., Ye, M., Lee, W.C.: Analyzing the spatial-semantic interaction of points of interest in volunteered geographic information. In: Egenhofer, M., Giudice, N., Moratz, R., Worboys, M. (eds.) COSIT 2011. LNCS, vol. 6899, pp. 350–370. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  14. Vandecasteele, A., Devillers, R.: Improving volunteered geographic data quality using semantic similarity measurements. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 1(1), 143–148 (2013)

    Article  Google Scholar 

  15. Schmid, F., Kutz, O., Frommberger, L., Kauppinen, T., Cai, C.: Intuitive and natural interfaces for geospatial data classification. In: Workshop on Place-Related Knowledge Acquisition Research (P-KAR), Kloster Seeon, Germany (2012)

    Google Scholar 

  16. Schmid, F., Frommberger, L., Cai, C., Dylla, F.: Lowering the barrier: How the what-you-see-is-what-you-map paradigm enables people to contribute volunteered geographic information. In: Proceedings of the 4th Annual Symposium on Computing for Development, p. 8. ACM (2013)

    Google Scholar 

  17. Schmid, F., Frommberger, L., Cai, C., Freksa, C.: What you see is what you map: Geometry-preserving micro-mapping for smaller geographic objects with mapit. In: Geographic Information Science at the Heart of Europe, pp. 3–19. Springer International Publishing (2013)

    Google Scholar 

  18. Arteaga, M.G.: Historical map polygon and feature extractor. In: Schmid, F., Kray, C. (eds.) Proceedings of ACM MapInteract, 1st International Workshop on Map Interaction. ACM (2013)

    Google Scholar 

  19. Neis, P., Zipf, A.: Analyzing the contributor activity of a volunteered geographic information project: The case of OpenStreetMap. ISPRS International Journal of Geo-Information 1(2), 146–165 (2012)

    Article  Google Scholar 

  20. Barron, C., Neis, P., Zipf, A.: A comprehensive framework for intrinsic OpenStreetMap quality analysis. Transactions in GIS 18 (2014)

    Google Scholar 

  21. Tobler, W.R.: A computer movie simulating urban growth in the detroit region. Economic Geography 46, 234–240 (1970)

    Article  Google Scholar 

  22. Devogele, T., Parent, C., Spaccapietra, S.: On spatial database integration. International Journal of Geographical Information Science 12(4), 335–352 (1998)

    Article  Google Scholar 

  23. Bishop, C.M.: Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus (2006)

    Google Scholar 

  24. Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques, 3rd edn. Morgan Kaufmann Publishers Inc., San Francisco (2011)

    Google Scholar 

  25. Cover, T., Hart, P.: Nearest Neighbor pattern classification. IEEE Transactions on Information Theory 13(1), 21–27 (1967)

    Article  MATH  Google Scholar 

  26. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)

    Google Scholar 

  27. Kohavi, R., et al.: A study of Cross-Validation and Bootstrap for accuracy estimation and model selection. In: Proc. International Joint Conference on Artificial Intelligence (IJCAI), pp. 1137–1145 (1995)

    Google Scholar 

  28. Fawcett, T.: An introduction to ROC analysis. Pattern Recognition Letters 27(8), 861–874 (2006)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Cognitive Systems Group, University of Bremen, Germany

    Ahmed Loai Ali & Falko Schmid

  2. SFB/TR 8 Spatial Cognition, University of Bremen, Germany

    Falko Schmid

  3. Faculty of Computers and Information, Assiut University, Egypt

    Ahmed Loai Ali

Authors
  1. Ahmed Loai Ali
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  2. Falko Schmid
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Editor information

Editors and Affiliations

  1. Department of Infrastructure Engineering, The University of Melbourne, 3010, Victoria, Australia

    Matt Duckham

  2. Institute for Geoinformatics (ifgi), University of Münster, Heisenbergstr. 2, 48149, Münster, Germany

    Edzer Pebesma

  3. Department of Geographical and Sustainability Sciences, The University of Iowa, 305 Jessup Hall, 52242, Iowa City, IA, USA

    Kathleen Stewart

  4. Department for Geodesy and Geoinformation Research Group Geoinformation, Vienna University of Technology, Gusshausstr. 27-29, 1040, Vienna, Austria

    Andrew U. Frank

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© 2014 Springer International Publishing Switzerland

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Ali, A.L., Schmid, F. (2014). Data Quality Assurance for Volunteered Geographic Information. In: Duckham, M., Pebesma, E., Stewart, K., Frank, A.U. (eds) Geographic Information Science. GIScience 2014. Lecture Notes in Computer Science, vol 8728. Springer, Cham. https://doi.org/10.1007/978-3-319-11593-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-11593-1_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11592-4

  • Online ISBN: 978-3-319-11593-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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