Description
Integrated into the 'BioDT Winter School & Hackathon,' this training session introduced TwinEco, a unified, dynamic, data-driven framework designed for ecological Digital Twins. The rgesource detailed how digital twins mirror real-world entities and processes in real time by linking observation, analysis, and decision-making. Attendees explored practical applications, including real-time deforestation tracking and prototype systems for managing invasive alien plant species.
Learning Objectives
By the end of this training module, learners will be able to:
- Comprehend the structural components, data flows, and architecture of Digital Twins within ecological contexts;
- Build and containerize data-driven workflows using NaaVRE to ensure portability and reproducibility across cloud environments;
- Structure, manage, and execute complex workflows efficiently.
Target Audience
The target audience consists of environmental researchers, bioinformaticians, software developers, and data managers interested in designing and using biodiversity-focused Digital Twins by leveraging high-performance infrastructures and scientific workflow environments.