ForestForward: visualizing and accessing integrated world forest data from the last fifty years

Abstract

DATABASE URL: https://forestforward.udl.cat Mitigating the effects of environmental exploitation on forests requires robust data analysis tools to inform sustainable management strategies and enhance ecosystem resilience. Access to extensive, integrated plant biodiversity data, spanning decades, is essential for this purpose. However, such data is often fragmented across diverse datasets with varying standards, posing two key challenges: first, integrating these datasets into a unified, well-structured data warehouse, and second, handling the vast volume of data using big data technologies to analyze and monitor the temporal evolution of ecosystems. To address these challenges, we developed and used an ETL (Extract, Transform, Load) protocol that curated and integrates 4,482 forestry datasets from around the world, dating back to the 18th century, into a 100GB data warehouse containing over 172 million records sourced from the GBIF (Global Biodiversity Information Facility) repository. We implemented Python scripts and a NoSQL MongoDB database to streamline and automate the ETL process, using the data warehouse to create the ForestForward web platform. ForestForward is a free, user-friendly application developed using the Django framework, which enables users to consult, download, and visualize the curated data. The platform allows users to explore data layers by year and observe the temporal evolution of ecosystems through visual representations.