Using and improving mapathon data through hackathons
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Date
Authors
Coetzee, Serena Martha
Rautenbach, Victoria
Green, Cameron
Gama, Kiev
Fourie, Nicolene
Goncalves, Breno Alencar
Sastry, Nishanth
Journal Title
Journal ISSN
Volume Title
Publisher
Copernicus Publications
Abstract
Geospatial data is essential for the development of the blue economy: for sustainable coastal management of coastal areas
and to unlock economic potential from marine and ocean resources. In developing countries, such as South Africa, there are
often gaps in the data with significant implications for the blue economy. We conducted a project aimed at addressing these
data gaps by experimenting with a circular process where geospatial data for selected areas on the South African coastline
were collected through mapathons and used in applications that were developed during hackathons. We validated this
circular approach with two iterations of mapathons and hackathons, and found that 1) the size and location of the map area
need to be carefully chosen; 2) those creating the apps needed a huge amount of help in dealing with the geospatial data; and
3) any geospatial data is useful for the blue economy, not only data with a very specific purpose in the blue economy
context, such as coastal access points. Overall, the geospatial data usability improved from one iteration to another and
would certainly improve if more iterations were added. Similar to the deployment of mapathons for disaster relief, future
research could focus on hosting hackathons for the rapid development of apps to assist with disaster relief operations.
Generally, the hosting of mapathons and hackathons in lockstep is a novel way of exposing students to interdisciplinary
collaboration in international teams with a common goal.
Description
Keywords
Crowdsourcing, Mapathon, Hackathon, OpenStreetMap
Sustainable Development Goals
Citation
Coetzee, S., Rautenbach, V., Green, C. et al. 2019, 'Using and improving mapathon data through hackathons', International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, no. 2/W13, pp. 1525-1529.