Describing Mexico Valley through Complex Data Integration

Urban phenomena in the Valley of Mexico have long been studied with a fragmented approach, often overlooking the intricate relationships between various contexts. This research laboratory addresses this gap by integrating data from sensor-based systems, government sources, and social media (complex data) into a cohesive methodological framework.

Our work combines sensor data with health statistics and social narratives to reflect community perceptions of urban phenomena across space and time. By merging these heterogeneous data sources, we aim to gain a comprehensive understanding of urban impacts at large-city, local, and social levels within the Valley of Mexico.

The primary goal is to integrate large datasets using a variety of methods, including Natural Language Processing, data mining, and Geographical Information Systems (GIS). These techniques allow us to uncover quantitative and qualitative patterns that emerge at different spatial scales and temporal resolutions, ultimately leading to a deeper understanding of urban phenomena.

Our laboratory's focus areas include the impact of air pollution, crime, public health, and the management of natural resources.

Dr. Roberto Zagal Flores