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ISPRS Int. J. Geo-Inf. 2015, 4(2), 535-550; doi:10.3390/ijgi4020535

Characterizing the Heterogeneity of the OpenStreetMap Data and Community

Faculty of Engineering and Sustainable Development, University of Gävle, SE-801 76 Gävle, Sweden
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Academic Editor: Wolfgang Kainz
Received: 6 January 2015 / Revised: 9 March 2015 / Accepted: 27 March 2015 / Published: 8 April 2015
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Abstract

OpenStreetMap (OSM) constitutes an unprecedented, free, geographical information source contributed by millions of individuals, resulting in a database of great volume and heterogeneity. In this study, we characterize the heterogeneity of the entire OSM database and historical archive in the context of big data. We consider all users, geographic elements and user contributions from an eight-year data archive, at a size of 692 GB. We rely on some nonlinear methods such as power law statistics and head/tail breaks to uncover and illustrate the underlying scaling properties. All three aspects (users, elements, and contributions) demonstrate striking power laws or heavy-tailed distributions. The heavy-tailed distributions imply that there are far more small elements than large ones, far more inactive users than active ones, and far more lightly edited elements than heavy-edited ones. Furthermore, about 500 users in the core group of the OSM are highly networked in terms of collaboration. View Full-Text
Keywords: OpenStreetMap; big data; power laws; head/tail breaks; ht-index OpenStreetMap; big data; power laws; head/tail breaks; ht-index
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Ma, D.; Sandberg, M.; Jiang, B. Characterizing the Heterogeneity of the OpenStreetMap Data and Community. ISPRS Int. J. Geo-Inf. 2015, 4, 535-550.

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