Trust as a Proxy Measure for the Quality of Volunteered Geographic Information i...
source link: https://link.springer.com/chapter/10.1007%2F978-3-319-00615-4_2
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
Trust as a Proxy Measure for the Quality of Volunteered Geographic Information in the Case of OpenStreetMap
- Carsten Keßler
- René Theodore Anton de Groot
- Carsten KeßlerEmail author
- René Theodore Anton de Groot
- 1.Institute for GeoinformaticsUniversity of MünsterMünsterGermany
- 40 Citations
- 1.5k Downloads
Abstract
High availability and diversity make Volunteered Geographic Information (VGI) an interesting source of information for an increasing number of use cases. Varying quality, however, is a concern often raised when it comes to using VGI in professional applications. Recent research directs towards the estimation of VGI quality through the notion of trust as a proxy measure. In this chapter, we investigate which indicators influence trust, focusing on inherent properties that do not require any comparison with a ground truth dataset. The indicators are tested on a sample dataset extracted from OpenStreetMap. High numbers of contributors, versions and confirmations are considered as positive indicators, while corrections and revisions are treated as indicators that have a negative influence on the development of feature trustworthiness. In order to evaluate the trust measure, its results have been compared to the results of a quality measure obtained from a field survey. The quality measure is based on thematic accuracy, topological consistency, and information completeness. To address information completeness as a criterion of data quality, the importance of individual tags for a given feature type was determined based on a method adopted from information retrieval. The results of the comparison between trust assessments and quality measure show significant support for the hypothesis that feature-level VGI data quality can be assessed using a trust model based on data provenance.
Keywords
Data Quality Ground Truth Data Volunteer Geographic Information Trust Assessment Data ConsumerReferences
- Artz D, Gil Y (2007) A survey of trust in computer science and the semantic web. Web Semant 5:58–71CrossRefGoogle Scholar
- Bishr M, Janowicz K (2010) Can we trust information?—The case of volunteered geographic information. In Devaraju A, Llaves A, Maué P, Keßler C (eds) Towards digital earth: search, discover and share geospatial data 2010. Workshop at future internet symposium, Sep 2010Google Scholar
- Bishr M, Kuhn W (2007) Geospatial information bottom-up: a matter of trust and semantics. In Fabrikant SI, Wachowicz M (eds) The European information society—leading the way with geo-information. Lecture Notes in Geoinformation and Cartography. Springer, Berlin Heidelberg, pp 365–387Google Scholar
- Bishr M, Mantelas L (2008) A trust and reputation model for filtering and classifying knowledge about urban growth. GeoJournal 72(3–4):229–237CrossRefGoogle Scholar
- Flanagin AJ, Metzger MJ (2008) The credibility of volunteered geographic information. GeoJournal 72(3):137–148CrossRefGoogle Scholar
- Golbeck JA (2005) Computing and applying trust in web-based social networks. Ph.D. thesis, University of Maryland. Available from http://drum.lib.umd.edu/bitstream/1903/2384/1/umi-umd-2244.pdf
- Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. GeoJournal 69(4):211–221CrossRefGoogle Scholar
- Haklay M (2010) How good is volunteered geographical information? a comparative study of OpenStreetMap and ordnance survey datasets. Environ Plann B, Plann Des 37(4):682–703CrossRefGoogle Scholar
- Haklay 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. Cartographic J 47(4):315–322CrossRefGoogle Scholar
- Helbich M, Amelunxen C, Neis P, Zipf A (2010) Investigations on locational accuracy of volunteered geographic information using OpenStreetMap data. GIScience 2010 Workshop on the role of volunteered geographic information in advancing science. Zurich, Switzerland. Available from http://ornl.org/sci/gist/workshops/2010/papers/Helbich.pdf
- International Organization for Standardization (2002) ISO Standard 19113:2002: Geographic information—quality principlesGoogle Scholar
- Jakobsson A, Giversen J (2009) Guidelines for implementing the ISO 19100 geographic information quality standards in national mapping and cadastral agencies. EuroGraphics 2009Google Scholar
- Kendall M (1938) A new measure of rank correlation. Biometrika 30(1–2):81–89Google Scholar
- Keßler C, Trame J, Kauppinen T (2011a) Provenance and trust in volunteered geographic information: the case of OpenStreetMap. Poster presentation, conference on spatial information theory, 12–16 Sep 2011, Belfast, Maine, USAGoogle Scholar
- Keßler C, Trame J, Kauppinen T (2011b) Tracking editing processes in volunteered geographic information: the case of OpenStreetMap. In Duckham M, Galton A, Worboys M (eds) Identifying objects, processes and events in spatio-temporally distributed data (IOPE), workshop at conference on spatial information theory 2011 (COSIT’11), 12 Sep 2011, Belfast, Maine, USAGoogle Scholar
- Koukoletsos T, Haklay M, Ellul C (2012) Assessing data completeness of VGI through an automated matching procedure for linear data. Trans GIS 16(4):477–498CrossRefGoogle Scholar
- Mezzetti N (2004) A socially inspired reputation model. In: Proceedings of 1st European PKI Workshop. Lecture Notes in Computer Science, vol 3093. Springer, pp 191–204Google Scholar
- Mooney P, Corcoran P (2012a) Who are the contributors to OpenStreetMap and what do they do?. In: Proceedings of 20th annual GIS research UK (GISRUK), Lancaster University, Apr 2012Google Scholar
- Mooney P, Corcoran P (2012b) Characteristics of heavily edited objects in OpenStreetMap. Future Internet 4(1):285–305CrossRefGoogle Scholar
- Mooney P, Corcoran P (2012c) The annotation process in OpenStreetMap. Trans GIS 16(4):561–579CrossRefGoogle Scholar
- Neis P, Zielstra D, Zipf A (2012) The street network evolution of crowdsourced maps: OpenStreetMap in Germany 2007–2011. Future Internet 4(1):1–21Google Scholar
- Salton G, Wong A, Yang CS (1975) A vector space model for automatic indexing. Commun ACM 18(11):613–620CrossRefGoogle Scholar
- Simmhan YL, Plale B, Gannon D (2005) A survey of data provenance in e-science. ACM Sigmod Rec 34(3):31–36CrossRefGoogle Scholar
- Sztompka P (1999) Trust: a sociological theory. Cambridge University Press, CambridgeGoogle Scholar
- van Exel M, Dias E, Fruijtier S (2010) The impact of crowdsourcing on spatial data quality indicators. GIScience 2010 workshop on the role of volunteered geographic information in advancing science. Zurich, Switzerland. Available from http://www.giscience2010.org/pdfs/paper_213.pdf
- Zielstra D, Zipf A (2010) A comparative study of proprietary geodata and volunteered geographic information for Germany. AGILE 2010. In: The 13th AGILE international conference on geographic information science. Guimarães, PortugalGoogle Scholar
Copyright information
About this chapter
- First Online 12 May 2013
- DOI https://doi.org/10.1007/978-3-319-00615-4_2
- Publisher Name Springer, Cham
- Print ISBN 978-3-319-00614-7
- Online ISBN 978-3-319-00615-4
- eBook Packages Earth and Environmental Science Earth and Environmental Science (R0)
Recommend
About Joyk
Aggregate valuable and interesting links.
Joyk means Joy of geeK