Anyone can contribute geographic information to OpenStreetMap (OSM), regardless of their level of experience or skills, which has raised concerns about quality. When reference data is not available to assess the quality of OSM data, intrinsic methods that assess the data and its metadata can be used. In this study, we applied unsupervised machine learning for analysing OSM history data to get a better understanding of who contributed when and how in Mozambique. Even though no absolute statements can be made about the quality of the data, the results provide valuable insight into the quality. Most of the data in Mozambique (93%) was contributed by a small group of active contributors (25%). However, these were less active than the OSM Foundation’s definition of active contributorship and the Humanitarian OpenStreetMap Team (HOT) definition for intermediate mappers. Compared to other contributor classifications, our results revealed a new class: contributors who were new in the area and most likely attracted by HOT mapping events during disaster relief operations in Mozambique in 2019. More studies in different parts of the world would establish whether the patterns observed here are typical for developing countries. Intrinsic methods cannot replace ground truthing or extrinsic methods, but provide alternative ways for gaining insight about quality, and they can also be used to inform efforts to further improve the quality. We provide suggestions for how contributor-focused intrinsic quality assessments could be further refined.

Informal settlements are a common occurrence in the South African landscape. These settlements are not planned and therefore lack conventional urban characteristics, such as street names and a regular grid or block structure, which are useful aids during wayfinding. As a result, it is difficult to navigate through such a settlement or to provide directions to a specific destination. The lack of street names also implies that directions provided by others play a more important role. In this paper, we present the results of a qualitative between-subjects study that assessed individuals’ wayfinding efficiency when using different types of directions in an informal settlement. Participants were divided into two groups of six participants each (3 males and 3 females). Two sets of directions were constructed for the same route, one based on left-right turn descriptors and landmarks, and the second based on cardinal directions and distances. The performance of participants was measured for each set of directions. Earlier studies reported that people preferred left-right directions but performed better when using cardinal directions. The results of our study show the opposite. We think that this is due to the lack of regular wayfinding aids in informal settlements, but further studies are required to confirm this. The results of our study are interesting for developers of navigational tools aimed at addressing the needs of people in informal settlements.