Technical Guidelines to Extract and Analyze VGI from Different Platforms

Levente Juhász, Adam Rousell and Jamal Jokar Arsanjani
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Levente Juhász: Geomatics Program, Fort Lauderdale Research and Education Center (FLREC), University of Florida, 3205 College Avenue, Fort Lauderdale, FL 33314, USA
Adam Rousell: GIScience Research Group, Heidelberg University, Im Neuenheimer Feld 348, Heidelberg 69120, Germany
Jamal Jokar Arsanjani: Geoinformatics Research Group, Department of Planning and Development, Aalborg University Copenhagen, A.C. Meyers Vænge 15, Copenhagen DK-2450, Denmark

Data, 2016, vol. 1, issue 3, 1-22

Abstract: An increasing number of Volunteered Geographic Information (VGI) and social media platforms have been continuously growing in size, which have provided massive georeferenced data in many forms including textual information, photographs, and geoinformation. These georeferenced data have either been actively contributed (e.g., adding data to OpenStreetMap (OSM) or Mapillary) or collected in a more passive fashion by enabling geolocation whilst using an online platform (e.g., Twitter, Instagram, or Flickr). The benefit of scraping and streaming these data in stand-alone applications is evident, however, it is difficult for many users to script and scrape the diverse types of these data. On 14 June 2016, a pre-conference workshop at the AGILE 2016 conference in Helsinki, Finland was held. The workshop was called “LINK-VGI: LINKing and analyzing VGI across different platforms”. The workshop provided an opportunity for interested researchers to share ideas and findings on cross-platform data contributions. One portion of the workshop was dedicated to a hands-on session. In this session, the basics of spatial data access through selected Application Programming Interfaces (APIs) and the extraction of summary statistics of the results were illustrated. This paper presents the content of the hands-on session including the scripts and guidelines for extracting VGI data. Researchers, planners, and interested end-users can benefit from this paper for developing their own application for any region of the world.

Keywords: Volunteered Geographic Information; OpenStreetMap; Flickr; Instagram; Mapillary (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2016
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