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ISPRS Int. J. Geo-Inf. 2016, 5(3), 37; doi:10.3390/ijgi5030037

A Framework for Data-Centric Analysis of Mapping Activity in the Context of Volunteered Geographic Information

Salzburg Research Forschungsgesellschaft m.b.H., Jakob-Haringer-Straße 5, 5020 Salzburg, Austria
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Academic Editors: Jamal Jokar Arsanjani, Ming-Hsiang (Ming) Tsou and Wolfgang Kainz
Received: 5 November 2015 / Revised: 8 February 2016 / Accepted: 22 February 2016 / Published: 15 March 2016
(This article belongs to the Special Issue Big Data for Urban Informatics and Earth Observation)
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Abstract

Over the last decade, volunteered geographic information (VGI) has become established as one of the most relevant geographic data sources in terms of worldwide coverage, representation of local knowledge and open data policies. Beside the data itself, data about community activity provides valuable insights into the mapping progress which can be useful for estimating data quality, understanding the activity of VGI communities or predicting future developments. This work proposes a conceptual as well as technical framework for structuring and analyzing mapping activity building on the concepts of activity theory. Taking OpenStreetMap as an example, the work outlines the necessary steps for converting database changes into user- and feature-centered operations and higher-level actions acting as a universal scheme for arbitrary spatio-temporal analyses of mapping activities. Different examples from continent to region and city-scale analyses demonstrate the practicability of the approach. Instead of focusing on the interpretation of specific analysis results, the work contributes on a meta-level by addressing several conceptual and technical questions with respect to the overall process of analyzing VGI community activity. View Full-Text
Keywords: volunteered geographic information; data analysis; mapping activity; framework volunteered geographic information; data analysis; mapping activity; framework
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

Rehrl, K.; Gröchenig, S. A Framework for Data-Centric Analysis of Mapping Activity in the Context of Volunteered Geographic Information. ISPRS Int. J. Geo-Inf. 2016, 5, 37.

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