## 4 Results
### Contributor Numbers and Activity Spectrums  
One of the most important factors of projects such as OSM that rely on volunteered data contributions is the activity of the community in the project. The active members do not only contribute new data but also keep existing data up to date or improve it over time. It was shown that an increasing number of contributors within an area also improve the positional accuracy of the geodata, one of many geodata quality assessment criteria [11]. Figure 2 shows the development of the OSM community for each urban area from January 2007 to September 2012. The absolute number of OSM members has been normalized by the population density in each urban area to reduce the impact of the size of the city area on the results. The urban area names appear next to Figure 2 in descending order based on the values retrieved from the datasets. The diagram shows that Berlin, Paris, Moscow and London have higher values in comparison to other urban areas that were tested when considering the relation between the number of OSM members and the total population density. Generally, there are three groups that can be distinguished. The four aforementioned cities fall into a group with the highest values, while Los Angeles and Sydney create the second group with average values. The third and last group inherits all other urban areas _i.e._, Johannesburg, Buenos Aires, Osaka, Istanbul, Seoul and Cairo with values smaller than 0.20. The statistical analysis showed, however, that there is no correlation between the number of contributors and the population density in the tested areas (Spearman's rho R\({}_{\mathrm{S}}\) value of \(-\)0.140). Figure 2 also shows the significantly different increase in member numbers for the different areas within the past four years. The urban areas showing the smallest values for current active contributors to the project also reveal the least impressive increase over time. Although the total number of OSM members in an area might give some prior impression about the potential data contributions that could occur in an area, it does not take the actual activity spectrum of the members into consideration. A smaller group of very active data contributors could achieve similar results in data collaboration efforts as a large group of mappers with very limited contributions. Thus, the following analysis divided the registered members for each urban area into different mapper groups  
Figure 2: Number of OpenStreetMap (OSM) Contributors per Population/Area-ratio (Jan. 2007–Sept. 2012). as introduced in a prior publication [16]. Different thresholds, based on the number of Nodes an OSM member created, helped to distinguish the different mapper groups. If a mapper created less than ten nodes she/he falls into the \"Nonrecurring Mapper\" group, less than 1000 Nodes identify \"Junior Mappers\" and more than 1000 Nodes identify mappers that are part of the \"Senior Mapper\" group. Figure 3a shows how many members have actively contributed to the project by making at least one edit (creation, modification or deletion) to an object, while Figure 3b shows the distribution of the members based on the aforementioned classification schema. The results presented in Figure 3a, representing the absolute numbers of OSM contributors, show a similar pattern as the relative values shown in Figure 2, with larger values for all European cities and Moscow. Seoul, Istanbul, and Cairo, the three urban areas with the highest population density values of all tested areas, do not show similarly high values for the number of contributors, indicating that population density is not a major factor for data contributor numbers in OSM. The vertical dashed lines in Figure 3b represent the average values for each corresponding mapper group for all areas. This additional information helps to prove that almost all urban areas, with the exception of Osaka, show similar distributions for the individual mapper groups.