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A Conceptual Quality Framework for Volunteered Geographic Information

  • Andrea Ballatore
  • Alexander Zipf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9368)

Abstract

The assessment of the quality of volunteered geographic information (VGI) is cornerstone to understand the fitness for purpose of datasets in many application domains. While most analyses focus on geometric and positional quality, only sporadic attention has been devoted to the interpretation of the data, i.e., the communication process through which consumers try to reconstruct the meaning of information intended by its producers. Interpretability is a notoriously ephemeral, culturally rooted, and context-dependent property of the data that concerns the conceptual quality of the vocabularies, schemas, ontologies, and documentation used to describe and annotate the geographic features of interest. To operationalize conceptual quality in VGI, we propose a multi-faceted framework that includes accuracy, granularity, completeness, consistency, compliance, and richness, proposing proxy measures for each dimension. The application of the framework is illustrated in a case study on a European sample of OpenStreetMap, focused specifically on conceptual compliance.

Keywords

Data quality Interpretability Conceptual quality Volunteered geographic information 

Notes

Acknowledgments

The authors thank Sophie Crommelinck and Sarah Labusga (University of Heidelberg) for the implementation of the case study, and the OpenStreetMap community for supplying the data.

References

  1. 1.
    Ballatore, A.: Defacing the map: cartographic vandalism in the digital commons. Cartographic J. 51(3), 214–224 (2014)CrossRefGoogle Scholar
  2. 2.
    Ballatore, A., Bertolotto, M.: Semantically enriching VGI in support of implicit feedback analysis. In: Tanaka, K., Fröhlich, P., Kim, K.S. (eds.) W2GIS 2011. LNCS, vol. 6574, pp. 78–93. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  3. 3.
    Ballatore, A., Bertolotto, M., Wilson, D.: Computing the semantic similarity of geographic terms using volunteered lexical definitions. Int. J. Geograph. Inf. Sci. 27(10), 2099–2118 (2013a)CrossRefGoogle Scholar
  4. 4.
    Ballatore, A., Wilson, D.C., Bertolotto, M.: A survey of volunteered open geo-knowledge bases in the semantic web. In: Pasi, G., Bordogna, G., Jain, L.C. (eds.) Quality Issues in the Management of Web Information. ISRL, vol. 50, pp. 93–120. Springer, Heidelberg (2013b) CrossRefGoogle Scholar
  5. 5.
    Barron, C., Neis, P., Zipf, A.: A comprehensive framework for intrinsic OpenStreetMap quality analysis. Trans. GIS 18(6), 877–895 (2014)CrossRefGoogle Scholar
  6. 6.
    Batini, C., Scannapieco, M.: Data Quality: Concepts, Methodologies and Techniques. Springer, Berlin (2006)Google Scholar
  7. 7.
    Bishr, M., Kuhn, W.: Trust and reputation models for quality assessment of human sensor observations. In: Tenbrink, T., Stell, J., Galton, A., Wood, Z. (eds.) COSIT 2013. LNCS, vol. 8116, pp. 53–73. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  8. 8.
    Burton-Jones, A., Storey, V., Sugumaran, V., Ahluwalia, P.: A semiotic metrics suite for assessing the quality of ontologies. Data Knowl. Eng. 55(1), 84–102 (2005)CrossRefGoogle Scholar
  9. 9.
    Si-said Cherfi, S., Akoka, J., Comyn-Wattiau, I.: Conceptual modeling quality - from EER to UML schemas evaluation. In: Spaccapietra, S., March, S.T., Kambayashi, Y. (eds.) ER 2002. LNCS, vol. 2503, pp. 414–428. Springer, Heidelberg (2002) CrossRefGoogle Scholar
  10. 10.
    Dodge, M., Kitchin, R.: Crowdsourced cartography: mapping experience and knowledge. Environ. Plan. A 45(1), 19–36 (2013)CrossRefGoogle Scholar
  11. 11.
    Flanagin, A.J., Metzger, M.J.: The credibility of volunteered geographic information. GeoJournal 72(3–4), 137–148 (2008)CrossRefGoogle Scholar
  12. 12.
    Frank, A.U.: Spatial communication with maps: defining the correctness of maps using a multi-agent simulation. In: Habel, C., Brauer, W., Freksa, C., Wender, K.F. (eds.) Spatial Cognition 2000. LNCS (LNAI), vol. 1849, pp. 80–99. Springer, Heidelberg (2000) CrossRefGoogle Scholar
  13. 13.
    Goodchild, M.F., Gopal, S.: The Accuracy of Spatial Databases. CRC Press, Boca Raton (1989) Google Scholar
  14. 14.
    Goodchild, M.F., Li, L.: Assuring the quality of volunteered geographic information. Spat. Stat. 1, 110–120 (2012)CrossRefGoogle Scholar
  15. 15.
    Guarino, N., Welty, C.A.: An overview of OntoClean. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, 2nd edn, pp. 201–220. Springer, Berlin (2009)CrossRefGoogle Scholar
  16. 16.
    Guarino, N., Oberle, D., Staab, S.: What is an ontology? In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, 2nd edn, pp. 1–17. Springer, Berlin (2009)CrossRefGoogle Scholar
  17. 17.
    Guptill, S., Morrison, J. (eds.): Elements of Spatial Data Quality. Elsevier, Oxford (1995)Google Scholar
  18. 18.
    Haklay, M.: How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environ. Plan. B Plan. Des. 37, 682–703 (2010)CrossRefGoogle Scholar
  19. 19.
    Haklay, M., Basiouka, S., Antoniou, V., Ather, A.: How many volunteers does it take to map an area well? The validity of Linus’ law to volunteered geographic information. Cartographic J. 47(4), 315–322 (2010)CrossRefGoogle Scholar
  20. 20.
    Heipke, C.: Crowdsourcing geospatial data. ISPRS J. Photogrammetry Remote Sens. 65(6), 550–557 (2010)CrossRefGoogle Scholar
  21. 21.
    Hunter, G., Bregt, A., Heuvelink, G., Bruin, S., Virrantaus, K.: Spatial data quality: problems and prospects. Research Trends in Geographic Information Science, LNGC, pp. 101–121. Springer, Berlin (2009)CrossRefGoogle Scholar
  22. 22.
    Kuhn, W.: Core concepts of spatial information for transdisciplinary research. Int. J. Geogr. Inf. Sc. 26(12), 2267–2276 (2012)CrossRefGoogle Scholar
  23. 23.
    Mooney, P., Corcoran, P.: Characteristics of heavily edited objects in OpenStreetMap. Future Internet 4(1), 285–305 (2012a)CrossRefGoogle Scholar
  24. 24.
    Mooney, P., Corcoran, P.: The annotation process in OpenStreetMap. Trans. GIS 16(4), 561–579 (2012b)CrossRefGoogle Scholar
  25. 25.
    Rosch, E.: Principles of categorization. In: Margolis, E., Laurence, S. (eds.) Concepts: Core Readings, pp. 189–206. MIT Press, Cambridge (1999)Google Scholar
  26. 26.
    Salgé, F.: Semantic accuracy. In: Guptill, S., Morrison, J. (eds.) Elements of Spatial Data Quality, pp. 139–151. Elsevier, Oxford (1995)CrossRefGoogle Scholar
  27. 27.
    Shi, W., Fisher, P., Goodchild, M.F. (eds.): Spatial Data Quality. CRC Press, Boca Raton (2003)Google Scholar
  28. 28.
    Solskinnsbakk, G., Gulla, J.A., Haderlein, V., Myrseth, P., Cerrato, O.: Quality of hierarchies in ontologies and folksonomies. Data Knowl. Eng. 74, 13–25 (2012)CrossRefGoogle Scholar
  29. 29.
    Stephens, M.: Gender and the GeoWeb: divisions in the production of user-generated cartographic information. GeoJournal 78(6), 981–996 (2013)CrossRefGoogle Scholar
  30. 30.
    Tartir, S., Arpinar, I., Moore, M., Sheth, A., Aleman-Meza, B.: OntoQA: metric-based ontology quality analysis. In: IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources, at the 5th IEEE International Conference on Data Mining 2005, ICDM 2005, pp. 1–9. IEEE (2005)Google Scholar
  31. 31.
    Van Damme, C., Hepp, M., Coenen, T.: Quality metrics for tags of broad folksonomies. In: Proceedings of International Conference on Semantic Systems (I-SEMANTICS), Graz, Austria, pp. 118–125 (2008)Google Scholar
  32. 32.
    Veregin, H.: Data quality measurement and assessment. NCGIA Core Curriculum in Geographic Information Science (1998). http://www.ncgia.ucsb.edu/giscc/units/u100/u100_f.html
  33. 33.
    Zielstra, D., Zipf, A.: A comparative study of proprietary geodata and volunteered geographic information for Germany. In: Painho, M., Santos, M.Y., Pundt, H. (eds.) Proceedings of the 13th AGILE International Conference on Geographic Information Science, pp. 1–15 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Center for Spatial StudiesUniversity of California, Santa BarbaraSanta BarbaraUSA
  2. 2.Geoinformatics Research Group, Department of GeographyUniversity of HeidelbergHeidelbergGermany

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