Data quality assurance for volunteered geographic information

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8728, Issue , 2014, Pages 126-141

  Ali, Ahmed Loai ^a,b   Schmid, Falko ^a  

^a UNIVERSITY OF BREMEN   (Germany)

^b ASSIUT UNIVERSITY   (Egypt)

Author keywords

[No Author keywords available]

Indexed keywords

QUALITY ASSURANCE; GEOGRAPHIC INFORMATION SYSTEMS;

DATA CORRECTIONS; GEOGRAPHIC INFORMATION; MACHINE LEARNING METHODS; QUALITY ISSUES; VOLUNTEERED GEOGRAPHIC INFORMATION;

LEARNING SYSTEMS;

EID: 84921502012     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-11593-1_9     Document Type: Article

References (28)

1. Goodchild, M.F.: Citizens as sensors: the world of volunteered geography. GeoJournal 69(4), 211–221 (2007)
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)
3. nd GEOValue Workshop, HafenCity University Hamburg, Germany, pp. 75–79 (2010)
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)
5. Girres, J.F., Touya, G.: Quality assessment of the french OpenStreetMap dataset. Transactions in GIS 14(4), 435–459 (2010)
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)
7. Neis, P., Zielstra, D., Zipf, A.: The street network evolution of crowdsourced maps: Open-StreetMap in Germany 2007–2011. Future Internet 4(1), 1–21 (2011)
8. Goodchild, M.F., Li, L.: Assuring the quality of volunteered geographic information. Spatial Statistics 1, 110–120 (2012)
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)
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)
11. Mooney, P., Corcoran, P.: The annotation process in OpenStreetMap. Transactions in GIS 16(4), 561–579 (2012)
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)
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)
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)
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)
16. Schmid, F., Frommberger, L., Cai, C.,Dylla, F.: Lowering the barrier: How the what-you-seeis-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)
17. Schmid, F., Frommberger, L., Cai, C., Freksa, C.:What you see is what you map: Geometrypreserving micro-mapping for smaller geographic objects with mapit. In: Geographic Information Science at the Heart of Europe, pp. 3–19. Springer International Publishing (2013)
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)
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)
20. Barron, C., Neis, P., Zipf, A.: A comprehensive framework for intrinsic OpenStreetMap quality analysis. Transactions in GIS 18 (2014)
21. Tobler, W.R.: A computer movie simulating urban growth in the detroit region. Economic Geography 46, 234–240 (1970)
22. Devogele, T., Parent, C., Spaccapietra, S.: On spatial database integration. International Journal of Geographical Information Science 12(4), 335–352 (1998)
23. Bishop, C.M.: Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus (2006)
24. Han, J., Kamber, M., Pei, J.: Data Mining: Concepts and Techniques, 3rd edn. Morgan Kaufmann Publishers Inc., San Francisco (2011)
25. Cover, T., Hart, P.: Nearest Neighbor pattern classification. IEEE Transactions on Information Theory 13(1), 21–27 (1967)
26. nd edn. Morgan Kaufmann, San Francisco (2005)
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)
28. Fawcett, T.: An introduction to ROC analysis. Pattern Recognition Letters 27(8), 861–874 (2006)