# A Reputation Model of OSM Contributor Based on Semantic Similarity of Ontology Concepts
## 6 Conclusions  
At present, volunteered geographic information has been widely used in many fields, but there are still some malicious, error-ridden, and low-quality data in volunteered geographic information due to the non-professional and non-standard contributors. Contributor's reputation has an important impact on geospatial data quality. However, there is a lack of study on the contributor's reputation based on semantic similarity of their contributions. In order to solve the existing problems and calculate the contributor's reputation more effectively, this paper draws on the ontology-related study in the field of knowledge and proposes a model of contributor's reputation evaluation based on semantic similarity of ontology concepts.  
The reputation model calculation is divided into two parts: initial reputation and evaluation reputation. The initial reputation is determined by the category of users classified based on improved WPCA feature dimension reduction and classification method. The evaluation relationship among users is based on their modification of OSM objectives, and the quantitative method of this evaluation relationship is designed. Firstly, by constructing geographic ontology, the semantic similarity is calculated on the basis of the feature similarity of ontology concept and the semantic distance of concept. Then, the contributor's reputation is evaluated by integrating the geometric similarity and topological similarity. Further, the initial reputation and evaluation reputation of users are combined to obtain their reputation. Finally, the historical data of OSM in Rutland, England, is used as an example to calculate the reputation of every user. The experimental results were evaluated by sampling analysis. The analysis results show that there is a positive correlation between data quality and contributors' reputation. In addition, it is proved that this model is a more effective method to evaluate data quality when semantic features change. It provides an effective metric to evaluate the semantic similarity between object versions for contributors' reputation evaluation.  
Conceptualization, Y.Z. and X.W.; methodology, Y.Z. and Y.L.; software, X.W.; validation, X.W.; formal analysis, Y.Z.; investigation, Y.Z.; resources, Y.Z.; data curation, X.W.; writing--original draft preparation, Y.Z. and X.W.; writing--review and editing, Y.Z., Y.L. and Z.L.; visualization, X.W.; supervision, Y.Z.; project administration, Y.Z.; funding acquisition, Y.Z., Y.L. and Z.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China grant number 41871320; Key Project of Hunan Provincial Education Department grant number 19A172; and Hunan Provincial Natural Science Foundation of China grant number 2021 JJ30276.  
Not applicable.  
The data presented in this study are openly available in Geofabrik at [[https://download.geofabrik.de/](https://download.geofabrik.de/)]([https://download.geofabrik.de/](https://download.geofabrik.de/)) (accessed on 28 July 2022).  
The authors would like to thank the editors and the reviewers for their contributions.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.