# A data-driven global observatory addressing worldwide challenges through text mining and complex data visualisation

## TL;DR

This paper introduces a global observatory that uses data and text mining to provide real-time insights on issues like epidemics and climate change.

## Contribution

A novel data-driven global observatory integrating diverse data sources and text mining for real-time global insights.

## Key findings

- The observatory provided real-time insights on the impact of the COVID-19 pandemic for decision-makers.
- The methodology was successfully applied to water resource management in the context of climate change.
- State-of-the-art machine learning methods captured global perspectives while considering local contexts.

## Abstract

Introduction: Observing the world on a global scale can help us understand better the context of problems that engage us all. Methods: In this paper, we propose a data-driven global observatory that puts together the different perspectives of media, science, statistics and sensing over heterogeneous data sources and text mining algorithms. Results: The implementation of this global observatory in the context of epidemic intelligence, monitoring the impact of the COVID-19 pandemic, allowed us to provide decision-makers with real-time insight from the data visualised through meaningful animations and interactive components. In the context of the climate change, we implemented the proposed methodology with a specific focus on water resource management, taking into consideration local configurations. Conclusion: This approach is able to capture through state-of-the-art machine learning methods the value of a global perspective on highly impactful topics, including local contexts and priorities as a configurable dimension.