Assessing the impact of demographic characteristics on spatial error in volunteered geographic information features
- 766 Downloads
The proliferation of volunteered geographic information (VGI), such as OpenStreetMap (OSM) enabled by technological advancements, has led to large volumes of user-generated geographical content. While this data is becoming widely used, the understanding of the quality characteristics of such data is still largely unexplored. An open research question is the relationship between demographic indicators and VGI quality. While earlier studies have suggested a potential relationship between VGI quality and population density or socio-economic characteristics of an area, such relationships have not been rigorously explored, and mainly remained qualitative in nature. This paper addresses this gap by quantifying the relationship between demographic properties of a given area and the quality of VGI contributions. We study specifically the demographic characteristics of the mapped area and its relation to two dimensions of spatial data quality, namely positional accuracy and completeness of the corresponding VGI contributions with respect to OSM using the Denver (Colorado, US) area as a case study. We use non-spatial and spatial analysis techniques to identify potential associations among demographics data and the distribution of positional and completeness errors found within VGI data. Generally, the results of our study show a lack of statistically significant support for the assumption that demographic properties affect the positional accuracy or completeness of VGI. While this research is focused on a specific area, our results showcase the complex nature of the relationship between VGI quality and demographics, and highlights the need for a better understanding of it. By doing so, we add to the debate of how demographics impact on the quality of VGI data and lays the foundation to further work.
KeywordsVolunteered geographic information OpenStreetMap Spatial analysis Spatial data quality Demographics
- Al-Bakri, M., & Fairbairn, D. (2010), Assessing the accuracy of ‘Crowdsourced’ data and its integration with official spatial data sets. In Proceedings of the 9th international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, pp. 317–320.Google Scholar
- Aske, D., Corman, R. R., & Marston, C. (2011). Education policy and school segregation: A study of the Denver metropolitan region. Journal of Legal, Ethical & Regulatory Issues, 14(2), 27–35.Google Scholar
- Burt, J., Barber, G., & Rigby, R. (2009). Elementary statistics for geographers (3rd ed.). New York, NY: Guilford Press.Google Scholar
- Cipeluch, B., Jacob, R., Winstanly, A., & Mooney, P. (2010). Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps. In Proceedings of the 9th international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, pp. 337–340.Google Scholar
- Coleman, D. J., Georgiadou, Y., & Labonte, J. (2009). Volunteered geographic information: The nature and motivation of produsers. International Journal of Spatial Data Infrastructures Research, 4(1), 332–358.Google Scholar
- Davis, J. (1973). Statistics and data analysis in geology. New York, NY: Wiley.Google Scholar
- de Smith, M. J., Goodchild, M. F., & Longley, P. A. (2007). Geospatial analysis: A comprehensive guide to principles, techniques and software tools (2nd ed.). Winchelsea, UK: The Winchelsea Press.Google Scholar
- Elwood, S., Goodchild, M. F., & Sui, D. (2013). Prospects for VGI research and the emerging fourth paradigm. In D. Sui, S. Elwood, & M. F. Goodchild (Eds.), Crowdsourcing geographic knowledge: Volunteered geographic information (VGI) in theory and practice (pp. 361–375). New York, NY: Springer.CrossRefGoogle Scholar
- Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically weighted regression & associated techniques. Chichester, UK: Wiley.Google Scholar
- Ghose, R., & Elwood, S. (2003). Public participation GIS and local political context: Propositions and research directions. URISA Journal, 15(2), 17–22.Google Scholar
- Hochmair, H. H., & Zielstra, D. (2013). Development and completeness of points of interest in free and proprietary data sets: A Florida case study. Creating the GISociety—Conference proceedings (pp. 39–48). Austria: Salzburg.Google Scholar
- Hudson-Smith, A., Crooks, A. T., Gibin, M., Milton, R., & Batty, M. (2009). Neogeography and Web 2.0: Concepts, tools and applications. Journal of Location Based Services, 3(2), 118–145.Google Scholar
- Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2010). Geographical information systems and science (3rd ed.). New York, NY: Wiley.Google Scholar
- McKechnie, J. (1983). Webster’s new twentieth century dictionary (2nd ed.). New York, NY: Simon and Schuster.Google Scholar
- Mooney, P., Corcoran, P., & Winstanley, A. (2010). Towards quality metrics for OpenStreetMap. In Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems, San Jose, CA, pp. 514–517.Google Scholar
- Nov, O., Arazy, O., & Anderson, D. (2011). Technology-mediated citizen science participation: A motivational model. In Proceedings of the 5th international AAAI conference on weblogs and social media, Barcelona, Spain.Google Scholar
- OpenStreetMap. (2013a). Tag: Amenity = school. http://wiki.openstreetmap.org/wiki/Tag:amenity%3Dschool. Accessed on 17 May 2013.
- OpenStreetMap. (2013b). USGS geographic names information system. http://wiki.openstreetmap.org/wiki/GNIS. Accessed on 17 May 2013.
- Poore, B. S., Wolf, E. B., Korris, E. M., Walter, J. L., & Matthews, G. D. (2012). Structures data collection for the national map using volunteered geographic information. U.S. Geological Survey open-file report 2012–1209, Reston, VA. http://pubs.usgs.gov/of/2012/1209.
- Schmidt, M., & Klettner, S. (2013). Gender and experience-related motivators for contributing to OpenStreetMap. Online proceedings of the international workshop on action and interaction in volunteered geographic information (ACTIVITY) at the 16th AGILE conference on geographic information science, Leuven, Belgium.Google Scholar
- Steinmann, R., Grochenig, S., Rehrl, K., & Brunauer, R. (2013). Contribution profiles of voluntary mappers in OpenStreetMap. Online proceedings of the international workshop on action and interaction in volunteered geographic information (ACTIVITY) at the 16th AGILE conference on geographic information science, Leuven, Belgium.Google Scholar
- Sui, D. (2008). The wikification of GIS and its consequences: Or Angelina Jolie’s new tattoo and the future of GIS. Computers, Environment and Urban Systems, 32(1), 1–5.Google Scholar
- The National Map. (2014). http://nationalmap.gov/TheNationalMapCorps/index.html. Accessed on 23 May 2014.
- U.S. Census Bureau. (2012). Geographic definitions. http://www.census.gov/geo/www/geo_defn.html#CensusTract. Accessed on 17 May 2013.
- Vickery, G., & Wunsch-Vincent, S. (2007). Participative web and user-created content: Web 2.0 wikis and social networking. Organization for Economic Cooperation and Development (OECD), Paris, France.Google Scholar
- Wong, D. W. S., & Lee, J. (2005). Statistical analysis of geographic information with ArcView GIS and ArcGIS. Hoboken, NJ: Wiley.Google Scholar
- Zielstra, D., & Zipf, A. (2010). A comparative study of proprietary geodata and volunteered geographic information for Germany. In Proceedings of the 13th AGILE international conference on geographic information science, Guimarães, Portugal, pp. 1–15.Google Scholar