LingOSM: Identifying the Cultural and Linguistic Influence on Mapping Behaviour
An Empirical Attempt to Substantiate the Sapir-Whorf-Hypothesis in Cartography using the Example of OpenStreetMap after the Nepal Earthquakes of 2015
OpenStreetMap Data are generated by a large and very diverse group of volunteers. Especially in the wake of disasters, people from all over the world are joining forces to provide current mapping information for the affected regions. The founding of the Humanitarian OpenStreetMap Team (HOT) has contributed significantly to channeling these efforts and organizing immediate and coordinated responses.
HOT tasks typically describe the area to be mapped, give specific instructions as to regional particularities, and pinpoint areas of particular importance. Since broad participation is encouraged and highly appreciated, the contributing mappers stem from all areas of the world.
To improve data quality and reliability, we are currently investigating the map data generated after the earthquakes in Nepal in spring 2015. A first investigation revealed a significant number of changes made to street classifications after the earthquake. To explore the reason behind those frequent changes we are currently investigating different factors influencing mapping behaviour. Our present approach is to investigate whether mappers with different linguistic backgrounds implement the HOT tasks differently, depending on their native language and/or their cultural background.
Linguistic research suggests that our mother language heavily influences the way we perceive and think about reality. However, so far the implications of this theory on international mapping cooperation have yet to be explored. If in fact native language does play a significant factor in individual mapping behaviour, such insights could be of great help to make HOT tasks more precise, i.e. by including linguistic and/or cultural hints or tips in the task description, hopefully further improving data quality and reliability.
To achieve this goal, we are investigating the street network of Nepal and the modifications/amendments added after the 2015 earthquakes. We are exploring all changes made to objects tagged with “highway=*” and will compare those changes to the linguistic and cultural background of the user responsible for the change.
Any and all information gathered in this context will be strictly confidential and results will be strictly anonymized and resulting papers will contain only aggregated data.