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GeoJournal

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The value of crowdsourced street-level imagery: examining the shifting property regimes of OpenStreetCam and Mapillary

  • Luis F. Alvarez LeonEmail author
  • Sterling Quinn
Article

Abstract

OpenStreetCam and Mapillary are two increasingly popular online services centered on providing street-level imagery through close association with the OpenStreetMap platform and crowdmapping community. While both services provide crowdsourced street-level imagery, the differences in their aims and operations present an opportunity to discuss the various ways in which commercialization dynamics and crowdmapping practices are reshaping each other in the geoweb. This is significant because crowdmapping relies on massive distributed pools of unpaid labor, and is often characterized by a discourse and identity of community-centered sharing that eschews profit-seeking as a central motive. While the use of OpenStreetMap by commercial products is not new, the emergence of crowdsourced street-level imagery is an innovation with significant consequences. Projects like Mapillary and OpenStreetCam have the potential to both change the collaborative dynamics that drive OpenStreetMap, and simultaneously disrupt the state of street-level imagery ecosystem, which has been dominated by a single private provider: Google Street View. In light of this, crowdourced street-level imagery should be assessed, not only in technical terms, but through the full range of its political-economic ramifications. To this end, in this article we examine the role of commercialization in crowdmapped street-level imagery through a property regimes framework. Using this approach, we identify, analyze, and critique the allocation of rights, roles, and economic value within these services, thus shedding light on the emergence of crowdsourced street-level imagery in the context of the geoweb, and the digital and ‘sharing’ economies.

Keywords

Crowdmapping Street-level imagery Geoweb Mapillary OpenStreetCam OpenStreetMap Google Street View Property regimes 

Notes

Compliance with ethical standards

Conflict of interest

The authors report no potential conflicts of interest related to this research.

Human and animal rights

No human or animal subjects were involved in the course of conducting this research.

References

  1. Alvarez León, L. F. (2016). Property regimes and the commodification of geographic information: An examination of Google Street View. Big Data & Society, 3(2), 2053951716637885.  https://doi.org/10.1177/2053951716637885.CrossRefGoogle Scholar
  2. Alvarez León, L. F., & Gleason, C. J. (2017). Production, property, and the construction of remotely sensed data. Annals of the American Association of Geographers, 107(5), 1075–1089.  https://doi.org/10.1080/24694452.2017.1293498.CrossRefGoogle Scholar
  3. Anguelov, D., Dulong, C., Filip, D., Frueh, C., Lafon, S., Lyon, R., et al. (2010). Google Street View: Capturing the World at Street Level. Computer, 43(6), 32–38.  https://doi.org/10.1109/MC.2010.170.CrossRefGoogle Scholar
  4. Barth, A. (2015). The paid mappers are coming. In State of the Map US 2015. Retrieved from http://stateofthemap.us/the-paid-mappers-are-coming/.
  5. Blackstone, W. (1893). Commentaries on the Laws of England in Four Books, vol. 1 [1753] (Commentaries on the Laws of England in Four Books. Notes selected from the editions of Archibold, Christian, Coleridge, Chitty, Stewart, Kerr, and others, Barron Field’s Analysis, and Additional Notes, and a Life of the Author by George Sharswood. In Two Volumes., Vol. I). Philadelphia: J.B. Lippincott Co.Google Scholar
  6. Brabham, D. C. (2012). The myth of amateur crowds. Information, Communication & Society, 15(3), 394–410.  https://doi.org/10.1080/1369118X.2011.641991.CrossRefGoogle Scholar
  7. Camboim, S. P., Bravo, J. V. M., & Sluter, C. R. (2015). An investigation into the completeness of, and the updates to, OpenStreetMap data in a heterogeneous Area in Brazil. ISPRS International Journal of Geo-Information, 4(3), 1366–1388.  https://doi.org/10.3390/ijgi4031366.CrossRefGoogle Scholar
  8. Caquard, S. (2014). Cartography II Collective cartographies in the social media era. Progress in Human Geography, 38(1), 141–150.CrossRefGoogle Scholar
  9. Creative Commons. (n.d.). Creative commons—Attribution-ShareAlike 4.0 International—CC BY-SA 4.0. Retrieved August 10, 2017, from https://creativecommons.org/licenses/by-sa/4.0/.
  10. Durward, D., Blohm, I., & Leimeister, J. M. (2016). Is there PAPA in crowd work? A Literature Review On Ethical Dimensions in crowdsourcing (pp. 823–832). IEEE.  https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0131.
  11. Elwood, S., Goodchild, M. F., & Sui, D. (2013). Prospects for VGI research and the emerging fourth paradigm. In Crowdsourcing geographic knowledge (pp. 361–375). Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-94-007-4587-2_20.
  12. Elwood, S., & Leszczynski, A. (2011). Privacy, reconsidered: New representations, data practices, and the geoweb. Geoforum, 42(1), 6–15.  https://doi.org/10.1016/j.geoforum.2010.08.003.CrossRefGoogle Scholar
  13. Elwood, S., & Leszczynski, A. (2012). New spatial media, new knowledge politics. Transactions of the Institute of British Geographers, 38(4), 544–559.  https://doi.org/10.1111/j.1475-5661.2012.00543.x.CrossRefGoogle Scholar
  14. Fisher, A. (2013, December 11). Google’s road map to global domination. Retrieved February 10, 2016, from http://www.nytimes.com/2013/12/15/magazine/googles-plan-for-global-domination-dont-ask-why-ask-where.html?_r=0.
  15. Gonzalez, M. (2017, December). Mejorando datos de caminos y carreteras usando OpenStreetCam. Technology presented at the State of the Map Latam 2017, Lima, Peru. Retrieved from https://www.slideshare.net/MiriamGonzalez49/mejorando-datos-de-caminos-y-carreteras-usando-openstreetcam.
  16. Goodchild, M. F. (2007). Citizens as sensors: Web 2.0 and the volunteering of geographic information. GeoFocus, 7(7), 8–10.Google Scholar
  17. Haklay, M. (2010). How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environment and Planning B: Planning and Design, 37(4), 682–703.  https://doi.org/10.1068/b35097.CrossRefGoogle Scholar
  18. Heller, M. A. (2000). Three faces of private property. Oregon Law Review, 79(2), 417–434.Google Scholar
  19. Hoffman, W. (n.d.). Ford sets sights on self-driving 3D mapping company with $6.6 million investment. Retrieved March 28, 2017, from https://www.inverse.com/article/18344-ford-civil-maps-autonomous-cars
  20. Hsu, S.-L. (2002). Two-dimensional framework for analyzing property rights regimes, A. UC Davis Law Review, 36(4), 813.Google Scholar
  21. Illisei, A., & Van Exel, M. (2016). OpenStreetView. Presented at the State of the Map US 2016, Seattle, Washington, USA. Retrieved from https://2016.stateofthemap.us/openstreetview/.
  22. Kocsis, D., & de Vreede, G.-J. (2016). Towards a Taxonomy of Ethical Considerations in Crowdsourcing. In AMCIS 2016 proceedings. Retrieved from https://aisel.aisnet.org/amcis2016/Virtual/Presentations/5.
  23. Lardinois, F. (2011, May 31). Microsoft Streetside Isn’t Just a Google Street View Clone Anymore. Retrieved August 7, 2017, from http://siliconfilter.com/microsoft-streetside-isnt-just-a-google-streetview-clone-anymore/.
  24. Leszczynski, A. (2012). Situating the geoweb in political economy. Progress in Human Geography, 36(1), 72–89.  https://doi.org/10.1177/0309132511411231.CrossRefGoogle Scholar
  25. Lin, Y.-W. (2011). A qualitative enquiry into OpenStreetMap making. New Review of Hypermedia and Multimedia, 17(1), 53–71.CrossRefGoogle Scholar
  26. Madrigal, A. C. (2012, September 6). How Google builds its mapsand what it means for the future of everything. Retrieved September 25, 2017, from https://www.theatlantic.com/technology/archive/2012/09/how-google-builds-its-maps-and-what-it-means-for-the-future-of-everything/261913/.
  27. Metz, R. (2014, February 28). Mapillary aims to build crowdsourced version of Google Street View. MIT Technology Review. Retrieved from https://www.technologyreview.com/s/525216/putting-crowdsourcing-on-the-map/.
  28. Microsoft Research. (2010). Microsoft research street slide view. Retrieved from https://www.youtube.com/watch?v=ktdhOv8E5lo.
  29. Neis, P., Zielstra, D., & Zipf, A. (2013). Comparison of volunteered geographic information data contributions and community development for selected world regions. Future Internet, 5(2), 282–300.  https://doi.org/10.3390/fi5020282.CrossRefGoogle Scholar
  30. Quinn, S. D., & MacEachren, A. M. (2018). A geovisual analytics exploration of the OpenStreetMap crowd. Cartography and Geographic Information Science, 45(2), 140–155.  https://doi.org/10.1080/15230406.2016.1276479.CrossRefGoogle Scholar
  31. Schlager, E., & Ostrom, E. (1992). Property-rights regimes and natural resources: A conceptual analysis. Land Economics, 68(3), 249–262.CrossRefGoogle Scholar
  32. Schmidt, F. A. (2013). The good, the bad and the ugly: Why crowdsourcing needs ethics (pp. 531–535). IEEE.  https://doi.org/10.1109/CGC.2013.89.
  33. Smith, C. (2013, September 5). Google + is the fourth most-used Smartphone App. Retrieved February 10, 2016, from http://www.businessinsider.com/google-smartphone-app-popularity-2013-9
  34. Solem, J. E. (2016, March 3). Announcing our $8M series a round. Retrieved June 20, 2017, from http://blog.mapillary.com/update/2016/03/03/funding.html.
  35. Stephens, M. (2013). Gender and the GeoWeb: Divisions in the production of user-generated cartographic information. GeoJournal, 78(6), 981–996.  https://doi.org/10.1007/s10708-013-9492-z.CrossRefGoogle Scholar
  36. Sui, D., & Goodchild, M. (2011). The convergence of GIS and social media: Challenges for GIScience. International Journal of Geographical Information Science, 25(11), 1737–1748.  https://doi.org/10.1080/13658816.2011.604636.CrossRefGoogle Scholar
  37. Telenav. (2016a, January 8). Terms and Conditions of Use. Effective as of August 1, 2016. Retrieved from http://openstreetcam.org/terms.
  38. Telenav. (2016b, September 22). Telenav releases OpenStreetView, an automotive-integrated open source platform designed to accelerate the advancement of OpenStreetMap. Retrieved August 24, 2017, from http://www.telenav.com/about/pr/pr-20160922.html.
  39. Van Exel, M. (2016, November 25). OpenStreetView is now OpenStreetCam. Retrieved August 24, 2017, from http://blog.improve-osm.org/en/2016/11/openstreetview-is-now-openstreetcam/.
  40. Vincent, L. (2007). Taking online maps down to street level. Computer, 40(12), 118–120.CrossRefGoogle Scholar
  41. Whitefield, M. (2016, September 26). 3-D images will allow users to get virtual view of Havana streets. Miami Herald. Retrieved from http://www.miamiherald.com/news/nation-world/world/americas/cuba/article104007501.html.
  42. Wilson, M. W., & Graham, M. (2013). Neogeography and volunteered geographic information: A conversation with Michael Goodchild and Andrew Turner. Environment and Planning A, 45(1), 10–18.  https://doi.org/10.1068/a44483.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Clark UniversityWorcesterUSA
  2. 2.Central Washington UniversityEllensburgUSA

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