Data meets people: Understanding OSM community activity with the ohsome framework
11-30, 11:00–12:30 (Africa/Douala), Room 1
Language: English

The OpenStreetMap project has evolved as a social product and forms a large community of people loosely connected through the joint work on a global geographic database. OSM is now used widely for applications such as web maps and navigation services and data from OSM has been used in domains such as urban planning [1], SDG monitoring [2], disaster management [3], public health [4], as well as during the COVID-19 pandemic [5].

In addition to contributions by individual volunteers (mappers), there is an intensifying trend that organized humanitarian [6] and corporate mapping communities contribute to OSM in general [7]. As of 2023 OSM is no longer an exclusive community of amateurs, but instead a community built of multiple smaller hobbyist, professional, amateur, and experienced mapping communities, in which professional stakeholders are sharply gaining influence on map data creation.

Recently, there have been discussions about a potential decline in OSM’s contributor base, e.g. [8] and [9]. We argue that it is important to better understand the various approaches to measure mapping activity. Together with the participants of our workshop, we want to discuss which measures are useful to understand “community health” and help to foster mapping motivation.

In this workshop we want to provide insights how we can measure and understand the evolution of the global and local OSM communities. We will provide several examples and hands-on exercise how the ohsome framework can be used to monitor mapping activity and community growth / stagnation / decline. For these examples we will prepare an online course book and jupyter notebooks, which can be used by the participants to run their own analyses and tackle their own research questions.

There is a need to integrate global and local perspectives about representation in OSM through interdisciplinary approaches. It has been outlined that it is not enough to describe the biased characteristics of map data or to simply assume that more data leads to better decisions and just transformations [10]. To overcome issues of representation, we argue that empowerment goes beyond involving local communities in the technical aspects of collecting map data.

We envision this workshop as a great opportunity to get in touch with OSM community members and learn more about their perspectives towards mapping in OSM and how to best build OSM communities. We would like to use some of the time of the workshop to form smaller groups (e.g. world cafe setting) to let as many people speak as possible and highlight diverse perspectives. As such we are looking forward to learn about the differences (and similarities) in OSM across continents and regions and how they could be measured from the “data perspective”.


[1] Milojevic-Dupont, N., Hans, N., Kaack, L. H., Zumwald, M., Andrieux, F., de Barros Soares, D., Lohrey, S., Pichler, P. P., and Creutzig, F. (2020). Learning from urban form to predict building heights. PLoS ONE, 15(12 December):1–22.

[2] Hoek, J. V. D., Friedrich, H. K., Ballasiotes, A., Peters, L. E. R., and Wrathall, D. (2021). Development after displacement: Evaluating the utility of openstreetmap data for monitoring sustainable development goal progress in refugee settlements. ISPRS International Journal of Geo-Information, 10:153.

[3] Scholz, S., Knight, P., Eckle, M., Marx, S., and Zipf, A. (2018). Volunteered Geographic Information for Disaster Risk Reduction—The Missing Maps Approach and Its Potential within the Red Cross and Red Crescent Movement. Remote Sensing, 10(8):1239.

[4] Bhatia, A., Mahmud, A., Fuller, A., Shin, R., Rahman, A., Shatil, T., Sultana, M., Morshed, K. A., Leaning, J., and Balsari, S. (2018). The Rohingya in cox’s bazar: When the stateless seek refuge. Health and Human Rights, 20(2):105–122.

[5] Marco Minghini, Serena Coetzee, Levente Juhasz, Godwin Yeboah, Peter Mooney, and A. Yair Grinberger (2020). Editorial: OpenStreetMap research in the COVID-19 era. Proceedings of the Academic Track at the State of the Map 2020, pages 1–4.

[6] Herfort, B., Lautenbach, S., Porto de Albuquerque, J., Anderson, J., and Zipf, A. (2021). The evolution of humanitarian mapping within the OpenStreetMap community. Scientific Reports, 11(1).

[7] Anderson, J., Sarkar, D., and Palen, L. (2019). Corporate Editors in the Evolving Landscape of OpenStreetMap. ISPRS International Journal of Geo-Information, 8(5):232.



[10] Porto de Albuquerque, J., Anderson, L., Calvillo, N., Coaffee, J., Cunha, M. A., Degrossi, L. C., Dolif, G., Horita, F., Klonner, C., Lima-Silva, F., Marchezini, V., Martins, M. H. d. M., Pajarito-Grajales, D., Pitidis, V., Rudorff, C., Tkacz, N., Traijber, R., and Zipf, A. (2021). The role of data in transformations to sustainability: a critical research agenda. Current Opinion in Environmental Sustainability, 49(August 2020):153–163.

Benjamin Herfort is researcher at HeiGIT and Heidelberg University. He has recently finished his PhD, for which he investigated questions of representation and data quality in OpenStreetMap from the perspectives of humanitarian and machine learning-assisted mapping in order to map what is not mapped. In his research and work he is furthermore dealing with the temporal evolution of OpenStreetMap data, MapSwipe and information from social media. He is developing open source tools and methods that incorporate geographic information systems for disaster management and humanitarian aid.