## 4 Future Trends  
This extensive review of previous research articles has shown that VGI and, especially, OSM have experienced a strong increase of interest within the research community over the past few years. Although an impressive number of research projects focused on the quality assessment and contributor analysis of VGI, questions remain about different research domains when considering the voluntarily contributed datasets. Most VGI data quality analyses in the past were conducted using a commercial or governmental reference dataset of high quality. While the general question remains whether these proprietary datasets can really be considered as more accurate than VGI, or if the opposite situation should be considered during the analysis, others focus on intrinsic data evaluations if no reference dataset exists or is not available, due to high costs or other factors. In the case of OSM, these intrinsic approaches included the evaluation of the number of edits or the number of contributors in a predefined area [21, 110, 114]. However, more research needs to be conducted to evaluate the effectiveness of these studies. If a number of contributors in OSM stopped collecting a certain feature type in a predefined area and starts collecting other information, does this imply that this particular object type is completely mapped in the area of interest or are there other criteria that can play a role? Additionally, particularly for quality assessment analyses, it would be necessary to have more detailed information about how the data was collected. Did the contributor use a GPS-device, the available areal imagery or is her/his contribution based on a data import? Although the OSM project provides several tags to specify the source or contribution type, the overall usage of those key/value-pairs is only limited within the community. Similarly, the discussion about trust in VGI is ongoing. Several studies have shown that VGI data can be used as an alternative to commercial or proprietary datasets and in the case of OSM, different companies already switched their mapping products to the freely available dataset. The credibility and trust in VGI plays a major role in these cases, but how can a VGI project, such as OSM, with no strict data specification or quality control, establish some type of trust? None of the previously conducted research projects considered one of the most important components of a VGI project: the individual contributor reputation. How can this reputation of a contributor be computed to provide a better understanding about the quality and trust of the data? What parameters are necessary to assess the quality of the contributions? Some first quantitative parameters, such as the amount of created or edited objects, have been investigated in prior studies to give some first insights. However, for a sophisticated trust estimation of a collaboratively collected dataset, other factors, such as the home location of a contributor, the mapping behavior, especially with regards to the usage of tags that represent a special area of interest of the contributor, or her/his acceptance and reputation within the community can play major roles. Would a contributor rating and reputation system, as discussed by [PERSON] and [PERSON] [12] and [PERSON] and [PERSON] [67], be useful to calculate the credibility and trust values as a proxy for VGI quality assessments? In one of the aforementioned studies, a method was introduced that created contributor profiles, such as \"Highway Mapper\" or \"Building Mapper\", based on the added information of the contributor [131]. A study about Wikipedia contributors revealed, however, a relation between the quality of an article and its authors and concluded that it is more important who contributes to the article and not as much what type of information was added [150]. Similar methods that separate contributors by their reputation and experience rather than the type of information they contribute are required for VGI projects. [PERSON] _et al_.