## 6 Conclusions  
In this work, we conducted a systematic study on how it is possible to reconstruct and maintain information about the infrastructure of cellular networks by making use of crowdsourced data sensed by mobile devices. Even though each generation of cellular networks is based on standard specifications, the task is far from being trivial, as each mobile operator adopts its own organization and makes some changes, usually not known by the external people. Nevertheless, comprehensive and reliable knowledge of the network is of primary importance in many fingerprint-based outdoor positioning tasks, ranging from navigation to contact tracing and emergency management.  
The gained knowledge was formally encoded by means of a conceptual database schema that is flexible enough to deal with several kinds of network technologies (and easily extendable to others) and able to accommodate crowdsourced measurements. This schema was then translated into a relational one, and subsequently implemented in a spatio-temporal database running on a PostgreSQL DBMS. The database was populated using two (distinct, although temporally overlapping) datasets, one public, obtained from the OpenCellD repository, and the other private, gathered from the company u-blox. As a result, the overall network information was reconstructed. Based on the collected data, we then showed how the system is capable of supporting several network-related tasks. Most importantly, it allows one to maintain an accurate and up-to-date representation of the network infrastructure, through the detection of inconsistent measurements coming from mobile devices, e.g., due to the violation of spatio-temporal constraints on their collection, and cell renaming phenomena. In addition, a selection of exemplary network analyses have been presented, ranging from basic ones to more complex spatial and temporal use cases. Overall, the proposed system poses as a solid basis to foster all kinds of tasks based on outdoor positioning and cellular network analysis.  
As for future work, given that our database structure is highly flexible and modular with respect to the considered network technologies, we plan to extend the spatio-temporal database with the support for 5G. In addition, to further promote network analyses, other datasets will be integrated within the database.  
Conceptualization, A.B., P.G., D.G. and N.S.; methodology, A.M. and D.G.; data curation, A.D.T.; writing, A.B., A.M. and N.S.; supervision, A.M. and A.D.T. All authors have read and agreed to the published version of the manuscript.  
Figure 20: Backtracking a cell-renaming operation. The two original cells are shown in red and blue.  
**Funding:** This research was funded by the company u-blox AG, projects \"Towards a uniform modeling framework for fingerprint-based positioning\" and \"Advanced solutions for indoor positioning.\"  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The authors would like to thank [PERSON] for his contribution to the development of the spatio-temporal database. Moreover, the authors acknowledge the work done by [PERSON] in his PhD dissertation, on which parts of the paper are based.  
**Conflicts of Interest:** The authors declare no conflict of interest.