Abstract
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.
This is a preview of subscription content, access via your institution.





References
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.
Andrews, D. T., Chen, L., Wentzell, P. D., & Hamilton, D. C. (1996). Comments on the relationship between principal components analysis and weighted linear regression for bivariate data sets. Chemometrics and Intelligent Laboratory Systems, 34(2), 231–244.
Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.
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.
Braun, M. T., & Oswald, F. L. (2011). Exploratory regression analysis: A tool for selecting models and determining predictor importance. Behavior Research Methods, 43(2), 331–339.
Brown, G., & Pullar, D. (2012). An evaluation of the use of points versus polygons in public participation geographic information systems using quasi-experimental design and Monte Carlo simulation. International Journal of Geographical Information Science, 26(2), 231–246.
Burt, J., Barber, G., & Rigby, R. (2009). Elementary statistics for geographers (3rd ed.). New York, NY: Guilford Press.
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.
Clark, P. J., & Evans, F. C. (1954). Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology, 35(4), 445–453.
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.
Crutcher, M., & Zook, M. (2009). Placemarks and waterlines: Racialized cyberscapes in Post-Katrina Google Earth. Geoforum, 40(4), 523–534.
Davis, J. (1973). Statistics and data analysis in geology. New York, NY: Wiley.
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.
Elwood, S. (2008). Volunteered geographic information: Key questions, concepts and methods to guide emerging research and practice. GeoJournal, 72(3–4), 133–135.
Elwood, S. (2009). Geographic information science: Emerging research on the societal implications of the geographical web. Progress in Human Geography, 34(3), 349–357.
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.
Fairbairn, D., & Al-Bakri, M. (2013). Using geometric properties to evaluate possible integration of authoritative and volunteered geographic information. ISPRS International Journal of Geo-Information, 2(2), 349–370.
Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically weighted regression & associated techniques. Chichester, UK: Wiley.
Ghose, R., & Elwood, S. (2003). Public participation GIS and local political context: Propositions and research directions. URISA Journal, 15(2), 17–22.
Girres, J.-F., & Touya, G. (2010). Quality assessment of the French OpenStreetMap dataset. Transactions in GIS, 14(4), 435–459.
Goodchild, M. F. (2007). Citizens as sensors: The world of volunteered geography. GeoJournal, 69(4), 211–221.
Goodchild, M. F., & Li, L. (2012). Assuring the quality of volunteered geographic information. Spatial Statistics, 1(1), 110–120.
Graham, S. D. (2005). Software-sorted geographies. Progress in Human Geography, 29(5), 562–580.
Haklay, M. (2010). How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environment and Planning B, 37(4), 682–703.
Haklay, M. 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. The Cartographic Journal, 47(4), 315–322.
Haklay, M., & Weber, P. (2008). Openstreetmap: User-generated street maps. IEEE Pervasive Computing, 7(4), 12–18.
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.
Holloway, T., Bozicevic, M., & Börner, K. (2007). Analyzing and visualizing the semantic coverage of Wikipedia and its authors. Complexity, 12(3), 30–40.
Huberty, C. J. (1984). Issues in the use and interpretation of discriminant analysis. Psychological Bulletin, 95(1), 156–171.
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.
Jackson, S. P., Mullen, W., Agouris, P., Crooks, A. T., Croitoru, A., & Stefanidis, A. (2013). Assessing completeness and spatial error of features in volunteered geographic information. ISPRS International Journal of Geo-Information, 2(2), 507–530.
James, F. J. (1986). A new generalized “Exposure-Based” segregation index demonstration in Denver and Houston. Sociological Methods & Research, 14(3), 301–316.
Kent, J. D., & Capello, H. T. (2013). Spatial patterns and demographic indicators of effective social media content during the Horsethief Canyon fire of 2012. Cartography and Geographic Information Science, 40(2), 78–89.
Koukoletsos, T., Haklay, M., & Ellul, C. (2012). Assessing data completeness of VGI through an automated matching procedure for linear data. Transactions in GIS, 16(4), 477–498.
Kuznetzov, S. (2006). Motivations of contributors to Wikipedia. ACM SIGCAS Computers and Society, 35(2), 1–7.
Li, L., Goodchild, M. F., & Xu, B. (2013). ‘Spatial. Temporal, and socioeconomic patterns in the use of Twitter and Flickr’, cartography and geographic information science, 40(2), 61–77.
Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2010). Geographical information systems and science (3rd ed.). New York, NY: Wiley.
Longley, P. A., & Singleton, A. D. (2009). Linking social deprivation and digital exclusion in England. Urban Studies, 46(7), 1275–1298.
McKechnie, J. (1983). Webster’s new twentieth century dictionary (2nd ed.). New York, NY: Simon and Schuster.
Mooney, P., & Corcoran, P. (2012). Characteristics of heavily edited objects in OpenStreetMap. Future Internet, 4(1), 285–305.
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.
Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1–2), 17–23.
Neis, P., Zielstra, D., & Zipf, A. (2011). The street network evolution of crowdsourced maps: OpenStreetMap in Germany 2007–2011. Future Internet, 4(1), 1–21.
Neis, P., & Zipf, A. (2012). Analyzing the contributor activity of a volunteered geographic information project—The case of OpenStreetMap. ISPRS International Journal of Geo-Information, 1(2), 146–165.
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.
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.
Oreg, S., & Nov, O. (2008). Exploring motivations for contributing to open source initiatives: The roles of contribution context and personal values. Computers in Human Behavior, 24(5), 2055–2073.
Over, M., Schilling, A., Neubauer, S., & Zipf, A. (2010). Generating Web-based 3D city models from OpenStreetMap: The current situation in Germany. Computers, Environment and Urban Systems, 34(6), 496–507.
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.
Porter, C. E., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999–1007.
Press, S. J., & Wilson, S. (1978). Choosing between logistic regression and discriminant analysis. Journal of the American Statistical Association, 73(364), 699–705.
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.
Sieber, R. (2006). Public participation geographic information systems: A literature review and framework. Annals of the Association of American Geographers, 96(3), 491–507.
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.
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.
The National Map. (2014). http://nationalmap.gov/TheNationalMapCorps/index.html. Accessed on 23 May 2014.
Tulloch, D. L. (2008). Is VGI participation? From vernal pools to video games. GeoJournal, 72(3–4), 161–171.
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.
Wheeler, D., & Tiefelsdorf, M. (2005). Multicollinearity and correlation among local regression coefficients in geographically weighted regression. Journal of Geographical Systems, 7(2), 161–187.
Wong, D. W. S., & Lee, J. (2005). Statistical analysis of geographic information with ArcView GIS and ArcGIS. Hoboken, NJ: Wiley.
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.
Zook, M. A., & Graham, M. (2007a). The creative reconstruction of the internet: Google and the privatization of cyberspace and DigiPlace. Geoforum, 38(6), 1322–1343.
Zook, M. A., & Graham, M. (2007b). Mapping DigiPlace: Geocoded internet data and the representation of place. Environment and Planning B, 34(3), 466–482.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mullen, W.F., Jackson, S.P., Croitoru, A. et al. Assessing the impact of demographic characteristics on spatial error in volunteered geographic information features. GeoJournal 80, 587–605 (2015). https://doi.org/10.1007/s10708-014-9564-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10708-014-9564-8