Articles | Volume 5
https://doi.org/10.5194/agile-giss-5-14-2024
https://doi.org/10.5194/agile-giss-5-14-2024
30 May 2024
 | 30 May 2024

Evaluating geotemporal behaviours of OpenStreetMap contributors

Guy Solomon, Dominick Sutton, Merve Polat Kayali, Xinyi Yuan, Zoe Gardner, and Ana Basiri

Keywords: Volunteered Geographic Information, crowdsourcing, OpenStreetMap, bias, user behaviour, gendered participation, disproportionate effect of COVID-19

Abstract. Volunteered Geographic Information (‘VGI’) and crowdsourcing are integral for projects such as Open- StreetMap (‘OSM’). However, despite the wide use of OSM as one of the most successful crowdsourcing platforms, the under-representation of certain demographic groups amongst those who contribute information may ultimately mean this information favours the interests of some groups over others. This can result in misleading conclusions for analyses conducted on the basis of these data. This paper connects OSM user contributions to demographic data collected via a survey. It shows that, in relation to geographic diversity of contributions, men and women demonstrate distinct trends over time. It then considers the extent to which this observed pattern can be seen as influenced by the COVID-19 pandemic. In this regard, it concludes that there does not appear to be a distinct ‘pandemic effect’ divergent from longer-term trends.

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