Analyzing Performance of Geographic Databases to Enhance Social Analysis in Map Applications
Year: 2025
Type: conference-paper
Abstract: Context: Social mapping applications are essential tools for understanding regional needs. In addition to physical geography, these maps integrate data on infrastructure, activities, and social demands— visualizing regions, points of interest, and relevant layers. This approach provides a clear and comprehensive view to support business, government, and social decisions. Problem: Managing social mapping data presents challenges, especially when storing sets of coordinates. This limits specialized database functions, impacting application performance in advanced geospatial functions. In particular, it is difficult to define which technologies are most appropriate to handle such data. Solution: We propose to use geographic databases such as PostgreSQL and MySQL Spatial. To do this, we propose to identify which functionalities are facilitated by these two technologies and compare their performance in executing these functionalities. IS Theory: Guided by the sociotechnical theory of Innovations Theory, this study examines how IS technologies interact in social contexts. Method: This study used a qualitative survey of professionals to propose functionalities considered useful for social analysis and an empirical experiment on the performance of the functionalities using PostGIS and MySQL Spatial databases. Results: Using a geographic database improved data processing, especially for large data. PostGIS showed better scalability and faster response times than MySQL Spatial as data volumes increased. Contributions and Impact on the IS field: This research improves the handling of geospatial data in IS, offering a practical solution to optimize queries, benefiting academia and industry.
Authors: Israel Silva, André Neto, Marcelle Mota
Institution: Universidade Federal do Pará
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410157933